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Javier Vazquez; Maria Vanrell; Ramon Baldrich | ||||
| Title | Towards a Psychophysical Evaluation of Colour Constancy Algorithms | Type | Conference Article | ||
| Year | 2008 | Publication | 4th European Conference on Colour in Graphics, Imaging and Vision Proceedings | Abbreviated Journal | |
| Volume | Issue | Pages | 372–377 | ||
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| Address | Terrassa (Spain) | ||||
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| Area | Expedition | Conference | CGIV08 | ||
| Notes | CAT;CIC | Approved | no | ||
| Call Number | CAT @ cat @ VVB2008a | Serial | 968 | ||
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| Author |
Javier Vazquez; Maria Vanrell; Anna Salvatella; Eduard Vazquez | ||||
| Title | A colour space based on the image content | Type | Book Chapter | ||
| Year | 2007 | Publication | Artificial Intelligence Research and Development, C. Angulo and L. Godo, pp 205–212 IOS Press | Abbreviated Journal | |
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ VVS2007 | Serial | 829 | ||
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| Author |
Javier Vazquez; J. Kevin O'Regan; Maria Vanrell; Graham D. Finlayson | ||||
| Title | A new spectrally sharpened basis to predict colour naming, unique hues, and hue cancellation | Type | Journal Article | ||
| Year | 2012 | Publication | Journal of Vision | Abbreviated Journal | VSS |
| Volume | 12 | Issue | 6 (7) | Pages | 1-14 |
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| Abstract | When light is reflected off a surface, there is a linear relation between the three human photoreceptor responses to the incoming light and the three photoreceptor responses to the reflected light. Different colored surfaces have different linear relations. Recently, Philipona and O'Regan (2006) showed that when this relation is singular in a mathematical sense, then the surface is perceived as having a highly nameable color. Furthermore, white light reflected by that surface is perceived as corresponding precisely to one of the four psychophysically measured unique hues. However, Philipona and O'Regan's approach seems unrelated to classical psychophysical models of color constancy. In this paper we make this link. We begin by transforming cone sensors to spectrally sharpened counterparts. In sharp color space, illumination change can be modeled by simple von Kries type scalings of response values within each of the spectrally sharpened response channels. In this space, Philipona and O'Regan's linear relation is captured by a simple Land-type color designator defined by dividing reflected light by incident light. This link between Philipona and O'Regan's theory and Land's notion of color designator gives the model biological plausibility. We then show that Philipona and O'Regan's singular surfaces are surfaces which are very close to activating only one or only two of such newly defined spectrally sharpened sensors, instead of the usual three. Closeness to zero is quantified in a new simplified measure of singularity which is also shown to relate to the chromaticness of colors. As in Philipona and O'Regan's original work, our new theory accounts for a large variety of psychophysical color data. | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ VOV2012 | Serial | 1998 | ||
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| Author |
Javier Vazquez; G. D. Finlayson; Maria Vanrell | ||||
| Title | A compact singularity function to predict WCS data and unique hues | Type | Conference Article | ||
| Year | 2010 | Publication | 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science | Abbreviated Journal | |
| Volume | Issue | Pages | 33–38 | ||
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| Abstract | Understanding how colour is used by the human vision system is a widely studied research field. The field, though quite advanced, still faces important unanswered questions. One of them is the explanation of the unique hues and the assignment of color names. This problem addresses the fact of different perceptual status for different colors.
Recently, Philipona and O'Regan have proposed a biological model that allows to extract the reflection properties of any surface independently of the lighting conditions. These invariant properties are the basis to compute a singularity index that predicts the asymmetries presented in unique hues and basic color categories psychophysical data, therefore is giving a further step in their explanation. In this paper we build on their formulation and propose a new singularity index. This new formulation equally accounts for the location of the 4 peaks of the World colour survey and has two main advantages. First, it is a simple elegant numerical measure (the Philipona measurement is a rather cumbersome formula). Second, we develop a colour-based explanation for the measure. |
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| Address | Joensuu, Finland | ||||
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| ISSN | ISBN | 9781617388897 | Medium | ||
| Area | Expedition | Conference | CGIV/MCS | ||
| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ VFV2010 | Serial | 1324 | ||
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| Author |
Javier Vazquez; C. Alejandro Parraga; Maria Vanrell; Ramon Baldrich | ||||
| Title | Color Constancy Algorithms: Psychophysical Evaluation on a New Dataset | Type | Journal Article | ||
| Year | 2009 | Publication | Journal of Imaging Science and Technology | Abbreviated Journal | |
| Volume | 53 | Issue | 3 | Pages | 031105–9 |
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| Abstract | The estimation of the illuminant of a scene from a digital image has been the goal of a large amount of research in computer vision. Color constancy algorithms have dealt with this problem by defining different heuristics to select a unique solution from within the feasible set. The performance of these algorithms has shown that there is still a long way to go to globally solve this problem as a preliminary step in computer vision. In general, performance evaluation has been done by comparing the angular error between the estimated chromaticity and the chromaticity of a canonical illuminant, which is highly dependent on the image dataset. Recently, some workers have used high-level constraints to estimate illuminants; in this case selection is based on increasing the performance on the subsequent steps of the systems. In this paper we propose a new performance measure, the perceptual angular error. It evaluates the performance of a color constancy algorithm according to the perceptual preferences of humans, or naturalness (instead of the actual optimal solution) and is independent of the visual task. We show the results of a new psychophysical experiment comparing solutions from three different color constancy algorithms. Our results show that in more than a half of the judgments the preferred solution is not the one closest to the optimal solution. Our experiments were performed on a new dataset of images acquired with a calibrated camera with an attached neutral grey sphere, which better copes with the illuminant variations of the scene. | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ VPV2009a | Serial | 1171 | ||
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| Author |
Javier Vazquez; C. Alejandro Parraga; Maria Vanrell | ||||
| Title | Ordinal pairwise method for natural images comparison | Type | Journal Article | ||
| Year | 2009 | Publication | Perception | Abbreviated Journal | PER |
| Volume | 38 | Issue | Pages | 180 | |
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| Abstract | 38(Suppl.)ECVP Abstract Supplement
We developed a new psychophysical method to compare different colour appearance models when applied to natural scenes. The method was as follows: two images (processed by different algorithms) were displayed on a CRT monitor and observers were asked to select the most natural of them. The original images were gathered by means of a calibrated trichromatic digital camera and presented one on top of the other on a calibrated screen. The selection was made by pressing on a 6-button IR box, which allowed observers to consider not only the most natural but to rate their selection. The rating system allowed observers to register how much more natural was their chosen image (eg, much more, definitely more, slightly more), which gave us valuable extra information on the selection process. The results were analysed considering both the selection as a binary choice (using Thurstone's law of comparative judgement) and using Bradley-Terry method for ordinal comparison. Our results show a significant difference in the rating scales obtained. Although this method has been used in colour constancy algorithm comparisons, its uses are much wider, eg to compare algorithms of image compression, rendering, recolouring, etc. |
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ VPV2009b | Serial | 1191 | ||
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| Author |
Javier Vazquez | ||||
| Title | Content-based Colour Space | Type | Report | ||
| Year | 2007 | Publication | CVC Technical Report #116 | Abbreviated Journal | |
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| Address | CVC (UAB) | ||||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ Vaz2007b | Serial | 828 | ||
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| Author |
Javier Vazquez | ||||
| Title | Colour Constancy in Natural Through Colour Naming and Sensor Sharpening | Type | Book Whole | ||
| Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Colour is derived from three physical properties: incident light, object reflectance and sensor sensitivities. Incident light varies under natural conditions; hence, recovering scene illuminant is an important issue in computational colour. One way to deal with this problem under calibrated conditions is by following three steps, 1) building a narrow-band sensor basis to accomplish the diagonal model, 2) building a feasible set of illuminants, and 3) defining criteria to select the best illuminant. In this work we focus on colour constancy for natural images by introducing perceptual criteria in the first and third stages.
To deal with the illuminant selection step, we hypothesise that basic colour categories can be used as anchor categories to recover the best illuminant. These colour names are related to the way that the human visual system has evolved to encode relevant natural colour statistics. Therefore the recovered image provides the best representation of the scene labelled with the basic colour terms. We demonstrate with several experiments how this selection criterion achieves current state-of-art results in computational colour constancy. In addition to this result, we psychophysically prove that usual angular error used in colour constancy does not correlate with human preferences, and we propose a new perceptual colour constancy evaluation. The implementation of this selection criterion strongly relies on the use of a diagonal model for illuminant change. Consequently, the second contribution focuses on building an appropriate narrow-band sensor basis to represent natural images. We propose to use the spectral sharpening technique to compute a unique narrow-band basis optimised to represent a large set of natural reflectances under natural illuminants and given in the basis of human cones. The proposed sensors allow predicting unique hues and the World colour Survey data independently of the illuminant by using a compact singularity function. Additionally, we studied different families of sharp sensors to minimise different perceptual measures. This study brought us to extend the spherical sampling procedure from 3D to 6D. Several research lines still remain open. One natural extension would be to measure the effects of using the computed sharp sensors on the category hypothesis, while another might be to insert spatial contextual information to improve category hypothesis. Finally, much work still needs to be done to explore how individual sensors can be adjusted to the colours in a scene. |
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Maria Vanrell;Graham D. Finlayson | |
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ Vaz2011a | Serial | 1785 | ||
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| Author |
Jaime Moreno; Xavier Otazu; Maria Vanrell | ||||
| Title | Local Perceptual Weighting in JPEG2000 for Color Images | Type | Conference Article | ||
| Year | 2010 | Publication | 5th European Conference on Colour in Graphics, Imaging and Vision and 12th International Symposium on Multispectral Colour Science | Abbreviated Journal | |
| Volume | Issue | Pages | 255–260 | ||
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| Abstract | The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM (Chromatic Induction Wavelet Model). | ||||
| Address | Joensuu, Finland | ||||
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| ISSN | ISBN | 9781617388897 | Medium | ||
| Area | Expedition | Conference | CGIV/MCS | ||
| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ MOV2010a | Serial | 1307 | ||
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| Author |
Jaime Moreno; Xavier Otazu; Maria Vanrell | ||||
| Title | Contribution of CIWaM in JPEG2000 Quantization for Color Images | Type | Conference Article | ||
| Year | 2010 | Publication | Proceedings of The CREATE 2010 Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 132–136 | ||
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| Abstract | The aim of this work is to explain how to apply perceptual concepts to define a perceptual pre-quantizer and to improve JPEG2000 compressor. The approach consists in quantizing wavelet transform coefficients using some of the human visual system behavior properties. Noise is fatal to image compression performance, because it can be both annoying for the observer and consumes excessive bandwidth when the imagery is transmitted. Perceptual pre-quantization reduces unperceivable details and thus improve both visual impression and transmission properties. The comparison between JPEG2000 without and with perceptual pre-quantization shows that the latter is not favorable in PSNR, but the recovered image is more compressed at the same or even better visual quality measured with a weighted PSNR. Perceptual criteria were taken from the CIWaM(ChromaticInductionWaveletModel). | ||||
| Address | Gjovik (Norway) | ||||
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| Area | Expedition | Conference | CREATE | ||
| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ MOV2010b | Serial | 1308 | ||
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Jaime Moreno; Xavier Otazu | ||||
| Title | Image compression algorithm based on Hilbert scanning of embedded quadTrees: an introduction of the Hi-SET coder | Type | Conference Article | ||
| Year | 2011 | Publication | IEEE International Conference on Multimedia and Expo | Abbreviated Journal | |
| Volume | Issue | Pages | 1-6 | ||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. The implementation of the proposed coder is developed for gray-scale and color image compression. Hi-SET compressed images are, on average, 6.20dB better than the ones obtained by other compression techniques based on the Hilbert scanning. Moreover, Hi-SET improves the image quality in 1.39dB and 1.00dB in gray-scale and color compression, respectively, when compared with JPEG2000 coder. | ||||
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| ISSN | 1945-7871 | ISBN | 978-1-61284-348-3 | Medium | |
| Area | Expedition | Conference | ICME | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MoO2011a | Serial | 2176 | ||
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| Author |
Jaime Moreno; Xavier Otazu | ||||
| Title | Image coder based on Hilbert scanning of embedded quadTrees | Type | Conference Article | ||
| Year | 2011 | Publication | Data Compression Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 470-470 | ||
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| Abstract | In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels. | ||||
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| Area | Expedition | Conference | DCC | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ MoO2011b | Serial | 2177 | ||
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| Author |
Jaime Moreno | ||||
| Title | Perceptual Criteria on Image Compresions | Type | Book Whole | ||
| Year | 2011 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Nowadays, digital images are used in many areas in everyday life, but they tend to be big. This increases amount of information leads us to the problem of image data storage. For example, it is common to have a representation a color pixel as a 24-bit number, where the channels red, green, and blue employ 8 bits each. In consequence, this kind of color pixel can specify one of 224 ¼ 16:78 million colors. Therefore, an image at a resolution of 512 £ 512 that allocates 24 bits per pixel, occupies 786,432 bytes. That is why image compression is important. An important feature of image compression is that it can be lossy or lossless. A compressed image is acceptable provided these losses of image information are not perceived by the eye. It is possible to assume that a portion of this information is redundant. Lossless Image Compression is defined as to mathematically decode the same image which was encoded. In Lossy Image Compression needs to identify two features inside the image: the redundancy and the irrelevancy of information. Thus, lossy compression modifies the image data in such a way when they are encoded and decoded, the recovered image is similar enough to the original one. How similar is the recovered image in comparison to the original image is defined prior to the compression process, and it depends on the implementation to be performed. In lossy compression, current image compression schemes remove information considered irrelevant by using mathematical criteria. One of the problems of these schemes is that although the numerical quality of the compressed image is low, it shows a high visual image quality, e.g. it does not show a lot of visible artifacts. It is because these mathematical criteria, used to remove information, do not take into account if the viewed information is perceived by the Human Visual System. Therefore, the aim of an image compression scheme designed to obtain images that do not show artifacts although their numerical quality can be low, is to eliminate the information that is not visible by the Human Visual System. Hence, this Ph.D. thesis proposes to exploit the visual redundancy existing in an image by reducing those features that can be unperceivable for the Human Visual System. First, we define an image quality assessment, which is highly correlated with the psychophysical experiments performed by human observers. The proposed CwPSNR metrics weights the well-known PSNR by using a particular perceptual low level model of the Human Visual System, e.g. the Chromatic Induction Wavelet Model (CIWaM). Second, we propose an image compression algorithm (called Hi-SET), which exploits the high correlation and self-similarity of pixels in a given area or neighborhood by means of a fractal function. Hi-SET possesses the main features that modern image compressors have, that is, it is an embedded coder, which allows a progressive transmission. Third, we propose a perceptual quantizer (½SQ), which is a modification of the uniform scalar quantizer. The ½SQ is applied to a pixel set in a certain Wavelet sub-band, that is, a global quantization. Unlike this, the proposed modification allows to perform a local pixel-by-pixel forward and inverse quantization, introducing into this process a perceptual distortion which depends on the surround spatial information of the pixel. Combining ½SQ method with the Hi-SET image compressor, we define a perceptual image compressor, called ©SET. Finally, a coding method for Region of Interest areas is presented, ½GBbBShift, which perceptually weights pixels into these areas and maintains only the more important perceivable features in the rest of the image. Results presented in this report show that CwPSNR is the best-ranked image quality method when it is applied to the most common image compression distortions such as JPEG and JPEG2000. CwPSNR shows the best correlation with the judgement of human observers, which is based on the results of psychophysical experiments obtained for relevant image quality databases such as TID2008, LIVE, CSIQ and IVC. Furthermore, Hi-SET coder obtains better results both for compression ratios and perceptual image quality than the JPEG2000 coder and other coders that use a Hilbert Fractal for image compression. Hence, when the proposed perceptual quantization is introduced to Hi-SET coder, our compressor improves its numerical and perceptual e±ciency. When ½GBbBShift method applied to Hi-SET is compared against MaxShift method applied to the JPEG2000 standard and Hi-SET, the images coded by our ROI method get the best results when the overall image quality is estimated. Both the proposed perceptual quantization and the ½GBbBShift method are generalized algorithms that can be applied to other Wavelet based image compression algorithms such as JPEG2000, SPIHT or SPECK. | ||||
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| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Xavier Otazu | |
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| ISSN | ISBN | 978-84-938351-3-2 | Medium | ||
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| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ Mor2011 | Serial | 1786 | ||
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| Author |
J. Nuñez; Xavier Otazu; M.T. Merino | ||||
| Title | A Multiresolution-Based Method for the Determination of the Relative Resolution between Images. First Application to Remote Sensing and Medical Images | Type | Journal | ||
| Year | 2005 | Publication | International Journal of Imaging Systems and Technology, 15(5): 225–235 (IF: 0.439) | Abbreviated Journal | |
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ NOM2005 | Serial | 645 | ||
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J. Nuñez; O. Fors; Xavier Otazu; Vicenç Pala; Roman Arbiol; M.T. Merino | ||||
| Title | A Wavelet-Based Method for the Determination of the Relative Resolution Between Remotely Sensed Images | Type | Journal | ||
| Year | 2006 | Publication | IEEE Transactions on Geoscience and Remote Sensing, 44(9): 2539–2548 | Abbreviated Journal | |
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ NFO2006 | Serial | 660 | ||
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| Author |
Ivet Rafegas; Maria Vanrell; Luis A Alexandre; G. Arias | ||||
| Title | Understanding trained CNNs by indexing neuron selectivity | Type | Journal Article | ||
| Year | 2020 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 136 | Issue | Pages | 318-325 | |
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| Abstract | The impressive performance of Convolutional Neural Networks (CNNs) when solving different vision problems is shadowed by their black-box nature and our consequent lack of understanding of the representations they build and how these representations are organized. To help understanding these issues, we propose to describe the activity of individual neurons by their Neuron Feature visualization and quantify their inherent selectivity with two specific properties. We explore selectivity indexes for: an image feature (color); and an image label (class membership). Our contribution is a framework to seek or classify neurons by indexing on these selectivity properties. It helps to find color selective neurons, such as a red-mushroom neuron in layer Conv4 or class selective neurons such as dog-face neurons in layer Conv5 in VGG-M, and establishes a methodology to derive other selectivity properties. Indexing on neuron selectivity can statistically draw how features and classes are represented through layers in a moment when the size of trained nets is growing and automatic tools to index neurons can be helpful. | ||||
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| Notes | CIC; 600.087; 600.140; 600.118 | Approved | no | ||
| Call Number | Admin @ si @ RVL2019 | Serial | 3310 | ||
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| Author |
Ivet Rafegas; Maria Vanrell | ||||
| Title | Color spaces emerging from deep convolutional networks | Type | Conference Article | ||
| Year | 2016 | Publication | 24th Color and Imaging Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 225-230 | ||
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| Abstract | Award for the best interactive session
Defining color spaces that provide a good encoding of spatio-chromatic properties of color surfaces is an open problem in color science [8, 22]. Related to this, in computer vision the fusion of color with local image features has been studied and evaluated [16]. In human vision research, the cells which are selective to specific color hues along the visual pathway are also a focus of attention [7, 14]. In line with these research aims, in this paper we study how color is encoded in a deep Convolutional Neural Network (CNN) that has been trained on more than one million natural images for object recognition. These convolutional nets achieve impressive performance in computer vision, and rival the representations in human brain. In this paper we explore how color is represented in a CNN architecture that can give some intuition about efficient spatio-chromatic representations. In convolutional layers the activation of a neuron is related to a spatial filter, that combines spatio-chromatic representations. We use an inverted version of it to explore the properties. Using a series of unsupervised methods we classify different type of neurons depending on the color axes they define and we propose an index of color-selectivity of a neuron. We estimate the main color axes that emerge from this trained net and we prove that colorselectivity of neurons decreases from early to deeper layers. |
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| Address | San Diego; USA; November 2016 | ||||
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| Area | Expedition | Conference | CIC | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ RaV2016a | Serial | 2894 | ||
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| Author |
Ivet Rafegas; Maria Vanrell | ||||
| Title | Colour Visual Coding in trained Deep Neural Networks | Type | Abstract | ||
| Year | 2016 | Publication | European Conference on Visual Perception | Abbreviated Journal | |
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| Address | Barcelona; Spain; August 2016 | ||||
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| Area | Expedition | Conference | ECVP | ||
| Notes | CIC | Approved | no | ||
| Call Number | Admin @ si @ RaV2016b | Serial | 2895 | ||
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