Abstract In images, the representation of glossiness, translucency, and roughness of material objects (Shitsukan) is essential for realistic image reproduction. To date, image coding has been developed considering various indices of the quality of the encoded image, for example,
the peak signal-to-noise ratio. Consequently, image coding methods that preserve subjective impressions of qualities such as Shitsukan have not been studied. In this study, the authors focus on the property of glossiness and propose a method of glossiness-aware image coding. Their purpose
is to develop an encoding algorithm that produces images that can be decoded by standard JPEG decoders, which are commonly used worldwide. The proposed method consists of three procedures: block classification, glossiness enhancement, and non-glossiness information reduction. In block classification,
the types of glossiness in a target image are classified using block units. In glossiness enhancement, the glossiness in each type of block is emphasized to reduce the amount of degradation of glossiness during JPEG encoding. The third procedure, non-glossiness information reduction, further
compresses the information while maintaining the glossiness by reducing the information in each block that does not represent the glossiness in the image. To test the effectiveness of the proposed method, the authors conducted a subjective evaluation experiment using paired comparison of images
coded by the proposed method and JPEG images with the same data size. The glossiness was found to be better preserved in images coded by the proposed method than in the JPEG images.
Improved compound image segmentation using automatic pixel block classification with SVM
