Optimal quantizer step sizes for transform coders

Hung, A.C.; Meng, Tao

doi:10.1109/icassp.1991.150939

Cited by 31 publications

(8 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It has long been realized that the current JPEG standard does not provide state-of-the-art coding performance. Several methods have been proposed to improve upon JPEG, including optimal Q-matrix design [8], [9], optimal thresholding [10], and joint optimization [11]. In Table I, we tabulate the coding results in PSNR of the baseline JPEG for Lena and Barbara.…”

Section: Dct-based Jpeg Image Codingmentioning

confidence: 99%

“…Such a coder is described in [14]. The observation in [14] is that an 8 8 DCT image representation can be thought of as a 64-subband decomposition, and that we can treat each 8 8 DCT block as a depth-three tree of coefficients. After Fig.…”

Section: B Dct-based Embedded Image Codingmentioning

confidence: 99%

“…Much better performance can be obtained with JPEG by optimal quantization matrix (Qmatrix) design [8], [9] and coefficient thresholding [10], while being compatible with the JPEG syntax. Note that, for the standard 512…”

Section: Introductionmentioning

confidence: 99%

“…It is well acknowledged that hardware (or software) implementation of the DCT is less expensive than that of the wavelet transform. For example, the most efficient algorithm for the two-dimensional (2-D) 8 8 DCT requires only 54 multiplications [12], while the complexity of calculating the discrete wavelet transform depends on the length of the wavelet filters, which is at least one multiplication per coefficient. We hence focus on the performance comparison of DCT-and wavelet-based coders in this paper.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A comparative study of DCT- and wavelet-based image coding

Xiong

Ramchandran

Orchard

et al. 1999

IEEE Trans. Circuits Syst. Video Technol.

180

View full text Add to dashboard Cite

Abstract-We undertake a study of the performance difference of the discrete cosine transform (DCT) and the wavelet transform for both image and video coding, while comparing other aspects of the coding system on an equal footing based on the state-of-theart coding techniques. Our studies reveal that, for still images, the wavelet transform outperforms the DCT typically by the order of about 1 dB in peak signal-to-noise ratio. For video coding, the advantage of wavelet schemes is less obvious. We believe that the image and video compression algorithm should be addressed from the overall system viewpoint: quantization, entropy coding, and the complex interplay among elements of the coding system are more important than spending all the efforts on optimizing the transform.Index Terms-Discrete cosine transform (DCT), image coding, video coding, wavelet transform.

show abstract

Section: Dct-based Jpeg Image Codingmentioning

confidence: 99%

Section: B Dct-based Embedded Image Codingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A comparative study of DCT- and wavelet-based image coding

Xiong

Ramchandran

Orchard

et al. 1999

IEEE Trans. Circuits Syst. Video Technol.

180

View full text Add to dashboard Cite

show abstract

“…In the variable rate quantizer case, the optimal quanitzer is entropy-constrained scalar quantizer (ECSQ) which can be obtained by minimizing D(Q) subjected to the entropy constraint H(Q) R c . Since designing an optimal ECSQ theoretically involves predetermining the statistical characteristic of the source signal and solving of a set of nonlinear equations [2][3][4][5] , it is still difficult to realize ECSQ in practice. Thus simple quantizer, such as the uniform scalar quantizer (USQ), is popular in many image and video compression standards, e.g.…”

Section: Introductionmentioning

confidence: 99%

A rate-distortion based quantization level adjustment algorithm in block-based video compression

Jiang

Wang

Sun

2009

J. Shanghai Jiaotong Univ. (Sci.)

View full text Add to dashboard Cite

In this paper, a rate-distortion based quantization level adjustment (RDQLA) algorithm is presented. Based on the rate-distortion criterion, the quantization level adjustment algorithm effectively improves coding efficiency by adaptively optimizing quantization levels of the signals near the boundaries of quantization cells and adjusting quantization levels per block. In addition, it has no overhead and is fully compatible with the existing compression standards. The proposed algorithm can be applied in any block based image and video coding method. In particular, the algorithm has been verified on the platform of H.264. Experimental results show that the proposed algorithm improves objective and subjective performances substantially. It is shown that the proposed algorithm has a gain of several dB comparing with the newest H.264 standard for high bit rates.

show abstract

A JPEG-like texture compression with adaptive quantization for 3D graphics application

Chen¹,

Lee²

2002

The Visual Computer

View full text Add to dashboard Cite

Optimal quantizer step sizes for transform coders

Cited by 31 publications

References 2 publications

A comparative study of DCT- and wavelet-based image coding

A comparative study of DCT- and wavelet-based image coding

A rate-distortion based quantization level adjustment algorithm in block-based video compression

A JPEG-like texture compression with adaptive quantization for 3D graphics application

Contact Info

Product

Resources

About