Surface fitting approach for reducing blocking artifacts in low bitrate DCT decoded images

Kieu, Van-Cuong; Nguyen, D.T.

doi:10.1109/icip.2001.958073

Cited by 6 publications

(6 citation statements)

References 9 publications

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“…16.1] and [13]. We shall not conduct the comparison with the methods proposed by [14], [18], [15] because: 1) the predictors F k for some range of k's proposed by [14] and [18] in the encoding stage require the values of F k themselves and hence the comparison in the encoding stage with our methods does not make sense; 2) the method in [15] needs an optimization by linear programming in order to predict the low frequency AC components of F , in addition to the same problem described in 1).…”

Section: A How Close U and U Q Are To F ?mentioning

confidence: 99%

“…Then the quantized coefficient matrix F Q is recovered via (15). Finally, the 2D inverse DCT (IDCT) is applied to F Q .…”

Section: A Brief Review Of the Lossy Jpeg Image Compression Standardmentioning

confidence: 99%

“…On the other hand, another set of techniques has been suggested as an option in the JPEG standard [1,Sec. 16.1] and further explored in [13], [14], [15]. These methods are all based on the prediction of the AC coefficients by fitting quadratic or cubic polynomial surface using the DC coefficients of several blocks.…”

Section: ) Dct Theoretically Approximates the Karhunen-loève Transfomentioning

confidence: 99%

“…Our methods can also be viewed as new and improved AC prediction methods over the previously proposed ones, e.g., [1,Sec. 16.1], [13], [14], [18], and [15].…”

Section: ) Dct Theoretically Approximates the Karhunen-loève Transfomentioning

confidence: 99%

“…From the viewpoint of prediction, there are several algorithms, [1,Sec. 16.1], [13], [14], [18], [15], which predict three to nine low frequency AC components of F . Therefore, in this section, we shall measure the performance of U and U Q as a predictor of F and compare the results with those obtained by [1,Sec.…”

Section: A How Close U and U Q Are To F ?mentioning

confidence: 99%

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Improvement of DCT-Based Compression Algorithms Using Poisson's Equation

Yamatani

Saito

2006

IEEE Trans. on Image Process.

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We propose two new image compression-decompression methods that reproduce images with better visual fidelity, less blocking artifacts, and better PSNR, particularly in low bit rates, than those processed by the JPEG Baseline method at the same bit rates. The additional computational cost is small, i.e., linearly proportional to the number of pixels in an input image. The first method, the "full mode" polyharmonic local cosine transform (PHLCT), modifies the encoder and decoder parts of the JPEG Baseline method. The goal of the full mode PHLCT is to reduce the code size in the encoding part and reduce the blocking artifacts in the decoder part. The second one, the "partial mode" PHLCT (or PPHLCT for short), modifies only the decoder part, and consequently, accepts the JPEG files, yet decompresses them with higher quality with less blocking artifacts. The key idea behind these algorithms is a decomposition of each image block into a polyharmonic component and a residual. The polyharmonic component in this paper is an approximate solution to Poisson's equation with the Neumann boundary condition, which means that it is a smooth predictor of the original image block only using the image gradient information across the block boundary. Thus the residual-obtained by removing the polyharmonic component from the original image block-has approximately zero gradient across the block boundary, which gives rise to the fast-decaying DCT coefficients, which in turn lead to more efficient compression-decompression algorithms for the same bit rates. We show that the polyharmonic component of each block can be estimated solely by the first column and row of the DCT coefficient matrix of that block and those of its adjacent blocks and can predict an original image data better than some of the other AC prediction methods previously proposed. Our numerical experiments objectively and subjectively demonstrate the superiority of PHLCT over the JPEG Baseline method and the improvement of the JPEG-compressed images when decompressed by PPHLCT. K. Yamatani is with the

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Section: A How Close U and U Q Are To F ?mentioning

confidence: 99%

“…Then the quantized coefficient matrix F Q is recovered via (15). Finally, the 2D inverse DCT (IDCT) is applied to F Q .…”

Section: A Brief Review Of the Lossy Jpeg Image Compression Standardmentioning

confidence: 99%

Section: ) Dct Theoretically Approximates the Karhunen-loève Transfomentioning

confidence: 99%

“…Our methods can also be viewed as new and improved AC prediction methods over the previously proposed ones, e.g., [1,Sec. 16.1], [13], [14], [18], and [15].…”

Section: ) Dct Theoretically Approximates the Karhunen-loève Transfomentioning

confidence: 99%