Zhiqun Gao

Bio: Zhiqun Gao is an academic researcher from Tianjin University. The author has contributed to research in topics: Image quality & Stereoscopy. The author has an hindex of 6, co-authored 11 publications receiving 202 citations.

Quality Index for Stereoscopic Images by Separately Evaluating Adding and Subtracting.

Abstract: The human visual system (HVS) plays an important role in stereo image quality perception. Therefore, it has aroused many people’s interest in how to take advantage of the knowledge of the visual perception in image quality assessment models. This paper proposes a full-reference metric for quality assessment of stereoscopic images based on the binocular difference channel and binocular summation channel. For a stereo pair, the binocular summation map and binocular difference map are computed first by adding and subtracting the left image and right image. Then the binocular summation is decoupled into two parts, namely additive impairments and detail losses. The quality of binocular summation is obtained as the adaptive combination of the quality of detail losses and additive impairments. The quality of binocular summation is computed by using the Contrast Sensitivity Function (CSF) and weighted multi-scale (MS-SSIM). Finally, the quality of binocular summation and binocular difference is integrated into an overall quality index. The experimental results indicate that compared with existing metrics, the proposed metric is highly consistent with the subjective quality assessment and is a robust measure. The result have also indirectly proved hypothesis of the existence of binocular summation and binocular difference channels.

New stereo shooting evaluation metric based on stereoscopic distortion and subjective perception

Abstract: In this paper, we examined the stereoscopic distortion by varying image acquisition parameters including but not limited to inter-camera distance, camera focal length, and shooting distance. Since a lot of new elements or problems about stereoscopic perception have not been considered or precisely defined before, an advanced shooting principle is raised in this paper to guarantee the overall quality of stereoscopic images. In this paper, based on stereoscopic distortion and features of camera configurations, we present new shooting formulae for both toed-in and parallel camera configurations. Besides, a new shooting evaluation metric is proposed for the evaluation of stereo camera quality. The experimental results show that the proposed approach can precisely assess the visual perception quality of stereo images according to the shooting parameters and can effectively evaluate the quality of stereo camera.

Perceptual image quality assessment: a survey

Abstract: Perceptual quality assessmentplays a vital role in the visual communication systems owing to theexistence of quality degradations introduced in various stages of visual signalacquisition, compression, transmission and display.Quality assessment for visual signals can be performed subjectively andobjectively, and objective quality assessment is usually preferred owing to itshigh efficiency and easy deployment. A large number of subjective andobjective visual quality assessment studies have been conducted during recent years.In this survey, we give an up-to-date and comprehensivereview of these studies.Specifically, the frequently used subjective image quality assessment databases are firstreviewed, as they serve as the validation set for the objective measures.Second, the objective image quality assessment measures are classified and reviewed according to the applications and the methodologies utilized in the quality measures.Third, the performances of the state-of-the-artquality measures for visual signals are compared with an introduction of theevaluation protocols.This survey provides a general overview of classical algorithms andrecent progresses in the field of perceptual image quality assessment.

A Self-Assessment Stereo Capture Model Applicable to the Internet of Things.

Abstract: The realization of the Internet of Things greatly depends on the information communication among physical terminal devices and informationalized platforms, such as smart sensors, embedded systems and intelligent networks. Playing an important role in information acquisition, sensors for stereo capture have gained extensive attention in various fields. In this paper, we concentrate on promoting such sensors in an intelligent system with self-assessment capability to deal with the distortion and impairment in long-distance shooting applications. The core design is the establishment of the objective evaluation criteria that can reliably predict shooting quality with different camera configurations. Two types of stereo capture systems—toed-in camera configuration and parallel camera configuration—are taken into consideration respectively. The experimental results show that the proposed evaluation criteria can effectively predict the visual perception of stereo capture quality for long-distance shooting.