Visual quality assessment of stereoscopic/3D images and videos has become an increasingly important and active field of research with the rapid growth in the quantity of stereoscopic/3D content created by the cinema, television, and entertainment industries. However, due to the diversity of stereoscopic/3D display technology and the complexity of human 3D perception, understanding the quality of experience (QoE) of stereoscopic/3D image and video is a difficult and multidisciplinary problem. Objective visual quality assessment attempts to quantify this subjective perception of visual QoE, utilizing tools from engineering, visual science, and psychology. In this chapter, first we discuss the challenges and difficulties one may face while trying to design and develop an effective objective quality assessment (QA) algorithm for stereoscopic images. This discussion is limited to “quality” where the stimulus being perceived is affected by some kind of distortions. In contrast to the success of a variety of objective QA algorithms for 2D images and videos, the field of stereoscopic image and video QA has been less successful in finding widely adopted quality measures. Most objective stereoscopic QA algorithms can be regarded as extensions of 2D QA algorithms, while few of them consider some aspects of depth perception and utilize either computed or measured depth/disparity information from the stereo pairs. We examine and analyze these stereoscopic QA algorithms, while focusing mainly on advances in exploiting natural scene statistics (NSS) and human visual system models in the design of stereoscopic QA algorithms. We also discuss recent work conducted on evaluating visual discomfort and fatigue when viewing stereoscopic images and videos—the more comprehensive “quality-of-experience” evaluation. Finally, we conclude the chapter with a discussion of possible future directions that the field of stereoscopic image and video QA may take. Our summary focuses on gaining a better understanding of depth/disparity sensation, using accurate and robust statistical models of natural stereo pairs, and performing a thorough analysis of various factors affecting the perception of stereoscopic distortions.

Visual Quality Assessment of Stereoscopic Image and Video: Challenges, Advances, and Future Trends

This paper surveys the results of various studies on 3-D image coding. Themes are focused on efficient compression and display-independent representation of 3-D images. Most of the works on 3-D image coding have been concentrated on the compression methods tuned for each of the 3-D image formats (stereo pairs, multi-view images, volumetric images, holograms and so on). For the compression of stereo images, several techniques concerned with the concept of disparity compensation have been developed. For the compression of multi-view images, the concepts of disparity compensation and epipolar plane image (EPI) are the efficient ways of exploiting redundancies between multiple views. These techniques, however, heavily depend on the limited camera configurations. In order to consider many other multi-view configurations and other types of 3-D images comprehensively, more general platform for the 3-D image representation is introduced, aiming to outgrow the framework of 3-D “image” communication and to open up a novel field of technology, which should be called the “spatial” communication. Especially, the light ray based method has a wide range of application, including efficient transmission of the physical world, as well as integration of the virtual and physical worlds. key words: 3-D image coding, stereo images, multi-view images, panoramic images, volumetric images, holograms, displayindependent representation, light rays, spatial communication

Compression and Representation of 3-D Images

SUMMARY This paper surveys the results of various studies on 3-D image coding. Themes are focused on efficient compression and display-independent representation of 3-D images. Most of the works on 3-D image coding have been concentrated on the compression methods tuned for each of the 3-D image formats (stereo pairs, multi-view images, volumetric images, holograms and so on). For the compression of stereo images, several techniques concerned with the concept of disparity compensation have been developed. For the compression of multi-view images, the concepts of disparity compensation and epipolar plane image (EPI) are the efficient ways of exploiting redundancies between multiple views. These techniques, however, heavily depend on the limited camera configurations. In order to consider many other multi-view configurations and other types of 3-D images comprehensively, more general platform for the 3-D image representation is introduced, aiming to outgrow the framework of 3-D “image” communication and to open up a novel field of technology, which should be called the “spatial” communication. Especially, the light ray based method has a wide range of application, including efficient transmission of the physical world, as well as

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INVITED PAPER Surveys on Image Processing Technologies - Algorithms, Sensors, and Applications - Compression and Representation of 3-D Images

This paper presents an improvement of the Visual Pattern image coding (VPIC) scheme presented by Chen and Bovik in (2) and (3). The patterns in this improved scheme are defined by morphological operations and classified by absolute error minimization. The improved scheme identifies more uniform blocks and reduces the noise effect. Therefore, it improves the compression ratio and image quality is steel preserved. To achieve a better compression ratio, a hierarchical approach based on the merging of uniform blocks is also described. Experimental results show that the improved scheme provides higher compression ratios compared to ordinary VPIC.

Visual pattern image coding by a morphological approach

This paper presents an improvement of the Visual Pattern image coding (VPIC) scheme presented by Chen and Bovik in [2] and [3] The patterns in this improved scheme are defined by morphological operations and classified by absolute error minimization The improved scheme identifies more uniform blocks and reduces the noise effect Therefore, it improves the compression ratio and image quality is steel preserved To achieve a better compression ratio, a hierarchical approach based on the merging of uniform blocks is also described Experimental results show that the improved scheme provides higher compression ratios compared to ordinary VPIC

https://www.ije.ir/article_71400_789181d861539de5b3688cc6ecfd8839.pdf

Visual Pattern Image Coding by a Morphological Approach (RESEARCH NOTE)

A binocular stereo system for images coded by visual pattern image coding (VPIC) is presented and evaluated. The use of VPIC for stereo vision applications is motivated by the capability of its coding primitives to reflect meaningful physical properties of projected real-scene surfaces: high-information edge regions and uniform regions. An algorithm for spatial matching of VPIC primitives is proposed. A dense disparity map is obtained and then used, together with one of the VPIC coded images of the stereo pair, to predict the second stereo image. The proposed stereo system allows a very high compression of the overall stereo information.

Stereo image compression using VPIC

A binocular stereo system for images coded by visual pattern image coding (VPIC) is presented and evaluated. The use of VPIC for stereo vision applications is motivated by the capability of its coding primitives to reflect meaningful physical properties of projected real-scene surfaces: high-information edge regions and uniform regions. An algorithm for spatial matching of VPIC primitives is proposed. It involves the solution of a complex optimization problem satisfying VPIC-related constraints. A dense disparity map is obtained and then used, together with one of the VPIC coded images of the stereo pair, to predict the second stereo image. The proposed stereo system allows a very high compression of the overall stereo information. Experimental results are presented to illustrate the performance of both stereo VPIC matching and predicting algorithms in natural images.

D. Craievich

Papers

Stereo image compression using VPIC

A stereo VPIC system