Chromatic filters for color vision deficiencies

Dissertação de mestrado em Optometria AvançadaAbout 10% of the population have some form of color vision deficiency. One of the most sever deficiencies is dichromacy. Dichromacy impairs color vision and impoverishes the discrimination of surface colors in natural scenes. Computational estimates based on hyperspectral imaging data from natural scenes suggest that dichromats can discriminate only about 7% of the number of colors discriminated by normal observers on natural scenes. These estimates, however, assume that the colors are equally frequent. Yet, pairs of color confused by dichromats may be rare and thus have small impact on the overall perceived chromatic diversity. By using an experimental setup that allows visual comparation between different spectra selected form hyperspectral images of natural scenes, it was estimated that the number of pairs that dichromats could discriminate was almost 70% of those discriminated by normal observers, a fraction much higher than anticipated from estimates of the number of discernible colors on natural scenes. Therefore, it may be rare for a dichromat to encounter two objects of different colors that he confounds. Thus, chromatic filters for color vision deficiencies intended to improve all colors in general may constitute low practical value. On this work it is proposed a method to compute filters specialized for a specific color-detection task, by taking into account the user’s color vision type, the local illuminant, and the reflectance spectra of the objects intended to be distinguished during that task. This method was applied on a case of a medical practitioner with protanopia to idealize a filter to improve detection of erythema on the skin of its patients. The filter improved the mean color difference between erythema and normal skin by 44%.Cerca de 10% da população possui alguma forma de deficiência de visão de cor. Uma das deficiências mais severas é a dicromacia. Dicromacia prejudica a visão das cores e empobrece a discriminação de superficies coloridas em cenas naturais. Estimativas computacionais baseadas em dados de imagens hiperespectrais de cenas naturais sugerem que dicromatas só pode discriminar cerca de 7% do número de cores discriminadas por observadores normais em cenas naturais. Estas estimativas, no entanto, assumem que todas as cores são igualmente frequentes. Contudo, pares de cores confundidos por dichromats podem ser raros e, portanto, têm pequeno impacto na diversidade cromática global percebida. Ao usar uma montagem experimental que permite comparação visual entre espectros diferentes selecionados a partir de imagens hiperespectrais de cenas naturais, estimou-se que o número de pares que dicromatas poderiam discriminar era quase 70% dos discriminados por observadores normais, uma fração muito maior do que o antecipado a partir de estimativas do número de cores percebidas em cenas naturais. Portanto, pode ser raro para um dicromat para encontrar dois objetos cujas cores ele confunda. Assim, filtros cromático para deficiências de visão das cores pretendidos para melhorar todas as cores em geral podem constituir baixo valor prático. Neste trabalho é proposto um método para calcular filtros especializados para uma tarefa específica de detecção de cor, tendo em conta o tipo de visão de cor do utilizador, o iluminante local, e os espectros de reflectancia dos objetos pretendidos a serem distinguidos durante essa tarefa. Este método foi aplicado em um caso de um médico com Protanopia para idealizar um filtro para melhorar a detecção de eritema na pele de seus pacientes. O filtro melhorou a diferença média de cor entre o eritema e a pele normal por 44%

Implicit knowledge of the colours of natural scenes matches real colours

Some studies suggest that there is a memory colour effect for familiar objects but whether this effect generalizes to natural scenes is unclear. Here we tested this hypothesis with an experiment where observers adjust the colour gamut of unknown natural scenes to produce realistic images. The stimuli were images of natural scenes unknown to the observers synthesized from hyperspectral imaging data. The images were rendered under D65 and could be manipulated to adjust the colour gamut in the CIELAB (a*, b*) by a multiplicative factor between 1.5 and 0.5. The images were presented on a calibrated CRT computer screen driven by a ViSaGe MKII. In the experiment the observers adjusted the gamut by actuating freely on a joy-pad. At the beginning of each trial each image was presented with its colour gamut compressed or expanded by a random factor. The task of the observers was to adjust the gamut such that the image appeared real. Data from five observers with normal colour vision shows that, on average, the gamut selected by observers was within 2% of the original one. These results suggest that observers have implicit unbiased knowledge of the colours of natural scenes.info:eu-repo/semantics/publishedVersio

The colors of natural scenes benefit dichromats

Dichromacy impairs color vision and impoverishes the discrimination of surface colors in natural scenes. Computational estimates based on hyperspectral imaging data from natural scenes suggest that dichromats can discriminate only about 10% of the colors discriminated by normal trichromats. These estimates, however, assume that the colors are equally frequent. Yet, pairs of colors confused by dichromats may be rare and thus have small impact on overall perceived chromatic diversity. This study estimated, empirically, how much dichromats are disadvantaged in discriminating surface colors drawn from natural scenes. The stimulus for the experiment was a scene made of real three-dimensional objects painted with matte white paint and illuminated by a spectrally tunable light source. In each trial the observers saw the scene illuminated by two spectra in two successive time intervals and had to indicate whether the colors perceived in the objects in the two intervals were the same or different. The spectra were drawn randomly from hyperspectral data of natural scenes and therefore represented natural spectral statistics. Four normal trichromats and four dichromats carried out the experiment. It was found that the number of pairs that could be discriminated by dichromats was almost 70% of those discriminated by normal trichromats, a proportion much higher than anticipated from estimates of discernible colors. Moreover, data from model simulations show that normal trichromats and dichromats use lightness differences for discrimination in about 40% and 50% of the discriminable pairs, respectively. Together these results suggest that the color distributions of natural scenes benefit the color vision of dichromats.- This work was supported by the Centro de Fisica of Minho University, by European Regional Development Fund (FEDER), Portugal through the COMPETE Program and by the Portuguese Foundation for Science and Technology (FCT), Portugal in the framework of the Strategic Funding UID/FIS/04650/2013 and by the project PTDC/MHC-PCN/4731/2012