Totally blind image quality assessment evaluator

Saifeldeen Abdalmajeed; Jiao Shuhong; Liu Wei

doi:10.1117/12.2050200

10 January 2014 Totally blind image quality assessment evaluator

Saifeldeen Abdalmajeed, Jiao Shuhong, Liu Wei

Proceedings Volume 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013); 90690M (2014) https://doi.org/10.1117/12.2050200
Event: Fifth International Conference on Graphic and Image Processing, 2013, Hong Kong, China

Abstract

Most general purpose no-reference image quality assessment algorithms need prior knowledge about anticipated distortions and their corresponding human opinion scores. One or more of distortion types may not be available when creating the model. In this paper, we develop a blind/no-reference opinion unaware distortion unaware image quality assessment algorithm based on natural scenes. The proposed approach extracts features in spatial domain for both natural images and distorted image at two scales, where locally normalized luminance values are modeled in two forms: pointwise for single pixels and pair-wise based log-derivative for the relationship of adjacent pixels. Then two sharpness functions are applied whose their outputs represent the extracted features of the proposed approach. Results show that the proposed algorithm correlates well with subjective opinion scores. They also show that the proposed algorithm outperforms the full-reference PSNR and SSIM methods. Not only do the results compete well with the recently developed NIQE model, but also outperform it.

Citation Download Citation

Saifeldeen Abdalmajeed, Jiao Shuhong, and Liu Wei "Totally blind image quality assessment evaluator", Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90690M (10 January 2014); https://doi.org/10.1117/12.2050200

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KEYWORDS

Image quality

Algorithm development

Feature extraction

Image compression

Databases

Image processing

Image segmentation

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