文献类型：期刊文献

英文题名：FS-BAND: A Frequency-Sensitive Banding Detector

作者：Chen, Zijian[1]; Sun, Wei[1]; Zhang, Zicheng[1]; Huang, Ru[2]; Lu, Fangfang[3]; Min, Xiongkuo[1]; Zhai, Guangtao[1]; Zhang, Wenjun[1]

机构：[1] Institue of Image Communication and Information Processing, Shanghai Jiao Tong University, China; [2] School of Information Science & Engineering, East China University of Science and Technology, China; [3] College of Computer Science and Technology, Shanghai University of Electric Power, China

年份：2023

外文期刊名：arXiv

收录：EI(收录号：20230445478)

语种：英文

外文关键词：Deep learning - Frequency domain analysis - Pixels - Quality of service

摘要：Banding artifact, as known as staircase-like contour, is a common quality annoyance that happens in compression, transmission, etc. scenarios, which largely affects the user’s quality of experience (QoE). The banding distortion typically appears as relatively small pixel-wise variations in smooth backgrounds, which is difficult to analyze in the spatial domain but easily reflected in the frequency domain. In this paper, we thereby study the banding artifact from the frequency aspect and propose a no-reference banding detection model to capture and evaluate banding artifacts, called the Frequency-Sensitive BANding Detector (FS-BAND). The proposed detector is able to generate a pixel-wise banding map with a perception correlated quality score. Experimental results show that the proposed FS-BAND method outperforms state-of-the-art image quality assessment (IQA) approaches with higher accuracy in banding classification task. ? 2023, CC BY.