Article

Blocking artifact detection and reduction in compressed data

Inf. Process. Lab., Aristotle Univ. of Thessaloniki
IEEE Transactions on Circuits and Systems for Video Technology (Impact Factor: 2.62). 11/2002; 12(10):877 - 890. DOI: 10.1109/TCSVT.2002.804880
Source: DBLP

ABSTRACT

A novel frequency-domain technique for image blocking artifact detection and reduction is presented. The algorithm first detects the regions of the image which present visible blocking artifacts. This detection is performed in the frequency domain and uses the estimated relative quantization error calculated when the discrete cosine transform (DCT) coefficients are modeled by a Laplacian probability function. Then, for each block affected by blocking artifacts, its DC and AC coefficients are recalculated for artifact reduction. To achieve this, a closed-form representation of the optimal correction of the DCT coefficients is produced by minimizing a novel enhanced form of the mean squared difference of slope for every frequency separately. This correction of each DCT coefficient depends on the eight neighboring coefficients in the subband-like representation of the DCT transform and is constrained by the quantization upper and lower bound. Experimental results illustrating the performance of the proposed method are presented and evaluated.

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Available from: George A. Triantafyllidis, Sep 10, 2013
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    • "They then took the ratio of number of coefficients between the two ranges as a distinguished feature to determine whether a given bitmap has been previously JPEG compressed. There are also several works [2] [3] that could be extended to identify decompressed bitmaps. However, the performance of these works is far from satisfactory, as reported in [12]. "
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    • "Because the blocking artefacts results in the abrupt changes of pixels across boundaries, a specific type of metric is required to measure such distortions. In addition to PSNR and SSIM, the M SDS t [15] (calculated on 16x16 block) was used to measure changes of intensity gradient of the pixels close to boundary of two blocks. For coarsely quantized blocks, a difference in the intensity gradient across the block boundary is expected to be larger than blocks which are not coarsely quantized. "
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    • "However, these methods usually investigate the JPEG images coded at low bit rates and aim to reduce the blocking artifacts between the block boundaries and ringing effect around the content edges due to the lossy JPEG compression. Some of them, e.g., [17]–[22], may be extended to identify JPEG images, however, the performances are very poor based on our experiments as shown in Section III-A. We also note that there are several reported methods, e.g., [6], [7], and [26]–[30], for other forensics/steganlysis issues which tried to identify the double JPEG compressed images and/or further estimate the primary quantization table. "
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