Blind noisy image quality assessment using block homogeneity

• We propose a blind image quality assessment approach using block homogeneity.
• We adaptively select homogeneous image regions to estimate noise statistics.
• We outperform conventional methods to achieve superior accuracy performance.

Blind noisy image quality assessment aims to evaluate the quality of the degraded noisy image without the need for the ground truth image. To tackle this challenge, this paper proposes an image quality assessment approach using block homogeneity. First, motivated by the local smoothness characteristic of the image, a block-based homogeneity measure is proposed to estimate the statistics (e.g., variance) of the noise incurred in the image, based on adaptively selected homogeneous image regions. Second, an image quality assessment approach is proposed by exploitie above-mentioned estimated noise variance, along with the visual masking effect of the human visual system. Experimental results are provided to demonstrate that the proposed image noise estimation approach yields superior accuracy and stability performance to that of conventional approaches, and the proposed image quality assessment approach achieves consistent performance to that of human subjective evaluation.

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