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No-reference image quality assessment based on localized discrete cosine transform for JPEG compressed images

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Abstract

In this paper, we propose a new no-reference image quality assessment for JPEG compressed images. In contrast to the most existing approaches, the proposed method considers the compression processes for assessing the blocking effects in the JPEG compressed images. These images have blocking artifacts in high compression ratio. The quantization of the discrete cosine transform (DCT) coefficients is the main issue in JPEG algorithm to trade-off between image quality and compression ratio. When the compression ratio increases, DCT coefficients will be further decreased via quantization. The coarse quantization causes blocking effect in the compressed image. We propose to use the DCT coefficient values to score image quality in terms of blocking artifacts. An image may have uniform and non-uniform blocks, which are respectively associated with the low and high frequency information. Once an image is compressed using JPEG, inherent non-uniform blocks may become uniform due to quantization, whilst inherent uniform blocks stay uniform. In the proposed method for assessing the quality of an image, firstly, inherent non-uniform blocks are distinguished from inherent uniform blocks by using the sharpness map. If the DCT coefficients of the inherent non-uniform blocks are not significant, it indicates that the original block was quantized. Hence, the DCT coefficients of the inherent non-uniform blocks are used to assess the image quality. Experimental results on various image databases represent that the proposed blockiness metric is well correlated with the subjective metric and outperforms the existing metrics.

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Notes

  1. Mean Opinion Score

  2. Differential Mean Opinion Score

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Correspondence to Hamid Hassanpour.

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Asadi Amiri, S., Hassanpour, H. & Marouzi, O.R. No-reference image quality assessment based on localized discrete cosine transform for JPEG compressed images. Multimed Tools Appl 77, 787–803 (2018). https://doi.org/10.1007/s11042-016-4246-9

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  • DOI: https://doi.org/10.1007/s11042-016-4246-9

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