Anumber of color image #delity metrics were evaluated by looking at howwell they predict visibility of image reproduction errors on perceptual image distortion maps. The image distortion maps are obtained empirically. Subjects examined image pairs consisting of an original and a reproduction. They marked locations on the reproduction that di#ered detectably from the original. We refer to the distribution of error marks by the subjects as image distortion maps. The empirically obtained image distortion maps are compared to the visible difference calculated using #1# the widely used root mean square error #point-by-point RMS# computed in uncalibrated RGB values, #2# the point-by-point CIELAB #E 94 values #CIE, 1994#, and #3# S-CIELAB #E 94 , a spatial extension of CIELAB #E metric. The uncalibrated RMS metric did not predict the perceptual image distortion data very well. The CIELAB #E 94 metric is a calibrated color #delity metric, and gave better predictions. The S-CIELAB metric, whi...

An effective image reproduction pipeline, spanning image capture, processing and display, must be designed to account for the properties of the human observer. In designing an image pipeline, three principles of human vision are particularly important: trichromacy, color adaptation, and pattern-color sensitivity. These properties also play an important role in metrics used to evaluate image quality reproduction. The main portion of this review comprises a description of these properties of the visual system and how these principles are incorporated into the image reproduction pipeline. The last part of this review describes a new image capture technology, based on a digital pixel fabricated on a CMOS process. This sensor is well-designed for exploring a novel image pipeline architecture that we call multiple-capture, single-image. This architecture is being developed to serve features of human vision that are not yet incorporated in the conventional pipeline. 1.

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In this paper we propose a new dataset for evaluation of image/video quality metrics with emphasis on applications in computer graphics. The proposed dataset includes LDR-LDR, HDR-HDR, and HDR-LDR reference-test video pairs with various types of distortions. We also present an example evaluation of recent image and video quality metrics that were applied in the field of computer graphics. In this evaluation all video sequences were shown on an HDR display, and subjects were asked to mark the regions where they saw differences between test and reference videos. As a result, we capture not only the magnitude of distortions, but also their spatial distribution. This has two advantages: on one hand the local quality information is valuable for computer graphics applications, on the other hand the subjectively obtained distortion maps are easily comparable to the maps predicted by quality metrics. 1.