Literature DB >> 27958425

Naturalness index for a tone-mapped high dynamic range image.

Yang Song, Gangyi Jiang, Mei Yu, Yun Zhang, Feng Shao, Zongju Peng.   

Abstract

High dynamic range (HDR) images can only be backward-compatible with existing low dynamic range (LDR) imaging systems after being processed by tone-mapping operators. Hence, the quality assessment (QA) of tone-mapped HDR images has become an important and challenging issue in HDR imaging research. In this paper, we propose a naturalness index for a tone-mapped image to predict its quality. First, we extract the statistical features of the tone-mapped image's luminance value and use it to evaluate the brightness naturalness with no reference information. Meanwhile, we use perceptive color, image contrast, and detail information to represent the image content and predict their naturalness qualities, respectively. Then, the four components of the naturalness qualities are combined to yield the overall naturalness quality of the tone-mapped image. Experimental results on a publicly available database demonstrated that, in comparison with a traditional LDR image QA method and a leading tone-mapped image QA method, the proposed method has better performance in evaluating a tone-mapped image's quality.

Year:  2016        PMID: 27958425     DOI: 10.1364/AO.55.010084

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  1 in total

1.  A Fully Convolutional Network-Based Tube Contour Detection Method Using Multi-Exposure Images.

Authors:  Xiaoqi Cheng; Junhua Sun; Fuqiang Zhou
Journal:  Sensors (Basel)       Date:  2021-06-14       Impact factor: 3.576

  1 in total

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