Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Evaluation of color differences in natural scene color images

Since there is a wide range of applications requiring image color difference (CD) assessment (e.g. color quantization, color mapping), a number of CD measures for images have been proposed. However, the performance evaluation of such measures often suffers from the following major flaws: (1) test images contain primarily spatial- (e.g. blur) rather than color-specific distortions (e.g. quantization noise), (2) there are too few test images (lack of variability in color content), and (3) test images are not publicly available (difficult to reproduce and compare). Accordingly, the performance of CD measures reported in the state-of-the-art is ambiguous and therefore inconclusive to be used for any specific color-related application. In this work, we review a total of twenty four state-of-the-art CD measures. Then, based on the findings of our review, we propose a novel method to compute CDs in natural scene color images. We have tested our measure as well as the state-of-the-art measures on three color related distortions from a publicly available database (mean shift, change in color saturation and quantization noise). Our experimental results show that the correlation between the subjective scores and the proposed measure exceeds 85% which is better than the other twenty four CD measures tested in this work (for illustration the best performing state-of-the-art CD measures achieve correlations with humans lower than 80%)

The Influence of media displays and image quality attributes for HDR image reproductions

High Dynamic Range (HDR) photography has been in existence at least since the time of Ansel Adams, with his experiments using analog film and darkroom techniques for the production of black and white prints in the 1940\u27s (Ashbrook, 2010). This photographic method has the ability to provide a more accurate representation of a scene through a greater range of the light and dark areas captured in an image. In the mid-20th century HDR Photography it has continued to grow in popularity among those interested in photography wishing to optimize their resulting image beyond a more commonly used technique. Presently, the limitations of commonly available reproduction technologies can lead to unpredictable output results through media such as monitor displays and inkjet prints. The purpose of this research was to determine the influence of quality attributes and image content on the preference of display media for HDR image reproductions. To achieve this purpose, a psychophysical experiment was conducted of 38 observers with previous imaging related exposure. This part of the study consisted of HDR comparisons across both a monitor display device and inkjet prints. Through qualitative and quantitative methods, common trends were identified among observer responses. The results show that for inkjet prints are the most preferred for the output of HDR images, specifically when printed on a metallic substrate. Additionally, the content of displayed images can directly impact display preference depending on the viewer\u27s perception and relationship formed with the photographic image. When evaluating HDR images across two media platforms, quality attributes comprising of a strong influence towards preference are sharpness, naturalness, contrast and highlights while artifacts, physical qualities and shadows were found to have barely any influence. Within the attributes related to HDR, relationships between attributes are found to be significant regarding image evaluation, leading to areas of further research

Color Constancy Adjustment using Sub-blocks of the Image

Extreme presence of the source light in digital images decreases the performance of many image processing algorithms, such as video analytics, object tracking and image segmentation. This paper presents a color constancy adjustment technique, which lessens the impact of large unvarying color areas of the image on the performance of the existing statistical based color correction algorithms. The proposed algorithm splits the input image into several non-overlapping blocks. It uses the Average Absolute Difference (AAD) value of each block’s color component as a measure to determine if the block has adequate color information to contribute to the color adjustment of the whole image. It is shown through experiments that by excluding the unvarying color areas of the image, the performances of the existing statistical-based color constancy methods are significantly improved. The experimental results of four benchmark image datasets validate that the proposed framework using Gray World, Max-RGB and Shades of Gray statistics-based methods’ images have significantly higher subjective and competitive objective color constancy than those of the existing and the state-of-the-art methods’ images