Titlebook: Stereoscopic Image Quality Assessment; Yong Ding,Guangming Sun Book 2020 Zhejiang University Press 2020 Stereoscopic image.Image quality a

可擴大

書目名稱Stereoscopic Image Quality Assessment影響因子(影響力)




書目名稱Stereoscopic Image Quality Assessment影響因子(影響力)學(xué)科排名




書目名稱Stereoscopic Image Quality Assessment網(wǎng)絡(luò)公開度




書目名稱Stereoscopic Image Quality Assessment網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Stereoscopic Image Quality Assessment被引頻次




書目名稱Stereoscopic Image Quality Assessment被引頻次學(xué)科排名




書目名稱Stereoscopic Image Quality Assessment年度引用




書目名稱Stereoscopic Image Quality Assessment年度引用學(xué)科排名




書目名稱Stereoscopic Image Quality Assessment讀者反饋




書目名稱Stereoscopic Image Quality Assessment讀者反饋學(xué)科排名

ARBOR

Brief Introduction on 2D Image Quality Assessment,are the accuracy of different IQA methods are provided. Finally, the general frameworks of 2D IQA methods containing full-reference (FR), reduced-reference (RR) and no-reference (NR) are illustrated based on specific algorithms.

CAMEO

Difference Between 2D and Stereoscopic Image Quality Assessment,ge quality assessment methods, SIQA needs considering complex binocular visual properties. The difference between SIQA and 2D IQA is introduced firstly in this chapter. Then stereoscopic image quality databases are listed and discussed detailedly. Finally, the general designed frameworks of SIQA methods are provided.

性冷淡

FAWN

Stereoscopic Image Quality Assessment Based on Binocular Combination,ly in this chapter. Then two region classification strategies to deal with no-matched pixels caused by different angles of two views are introduced. Finally, visual fatigue and visual discomfort prediction models are developed to simulate the negative influence of non-corresponding areas in stereo pairs.

裝飾

Stereoscopic Image Quality Assessment Based on Human Visual System Properties,detail. Visual attention, as one of the most important mechanisms of the HVS, is clarified clearly and some Stereoscopic Image Quality Assessments (SIQA) methods based on visual saliency are also presented. In the end of this chapter, Just Noticeable Difference (JND) model and corresponding IQA methods are introduced.

寬度

Book 2020ics, stereo vision and deep learning. It covers the fundamentals of stereoscopic image quality assessment (SIQA), the relevant engineering problems and research significance, and also offers an overview of the significant advances in visual quality assessment for stereoscopic images, discussing and

Cerebrovascular

COWER

敲竹杠

Introduction, few years, a variety of IQA methods have been introduced and they can be divided into three categories: full-reference IQA, reduced-reference IQA and no-reference IQA. All of these methods are clarified in detail in this book. In this chapter, the overall structure of the book is explained briefly