The RIT–DuPont visual color-difference data as the RIT–DuPont data set, and they are the basis for [Color Res. Appl. 16, 297–316 (1991)] have been used our current analyses. to estimate contours of equal color-differences (ellipThe RIT–DuPont data set consists of 156 tolerances, soids) at 19 color centers, in CIELAB and x , y , Y /100 each of equal visual color difference, DV . Nineteen color c...

A large scale psychophysical experiment was carried out to judge the perception of image quality of the photographic images. Two types of experiments, pair comparison and categorical judgment, were conducted for evaluating image difference and absolute quality respectively. Test images were generated by rendering the eight selected original images according to the change of lightness, chroma, c...

In this study, we evaluated the effect that pixel size has upon people’s preferences for images. We used multispectral images of faces as the scene data and simulated the response from sensors with different pixel size while the other sensor parameters were kept constant. Subjects were asked to choose between pairs of images; we found that preference judgments were primarily influenced by the v...

The world of color image difference modeling can be considered relatively young, when compared with the rich history of general color difference equations. While young, this area of research is well beyond the primordial soup stage. In this paper we present a framework for describing the evolution of color image difference models. This framework builds upon the S-CIELAB model, which in turn was...

We propose two novel image difference metrics using an extension of the S-CIELAB framework, which are based on the Difference of Gaussians model. The first metric uses the Difference of Gaussians model as a basis for the spatial filtering with the ∆E ab as a color difference formula, while the second uses the same model in association with the ∆EE color difference formula. A dataset with 20 gam...

Skin color is a simple but powerful pixel based feature. Skin color has proven to be a useful and sturdy cue for face detection, localization and tracking, hand detection, etc. Skin color is a useful means for human face detection. In this paper, we propose two color spaces YCbCr and CIELab and compare the results of both color space. Analyze the efficient method for skin color segmentation und...

The quality of several colour image difference metrics, pixelwise CIELAB DEab, S-CIELAB, iCAM, Structural Similarity Index, Universal Image Quality and the hue-angle algorithm, have been investigated. These results were compared with the results from a psychophysical experiment in which the perceptual image difference was evaluated. Six original images were reproduced using six different colour...

Spatial resolution is a key parameter in many applications of image processing. In order to improve the spatial resolution we make use of super resolution algorithms. In this paper an SR image reconstruction algorithm is proposed using Integer wavelet transform (IWT) and Bit plane technique (BTP). The proposed method is analyzed in different color space transforms such as RGB, Ycbcr and CIELAB ...