A low-complexity modeling approach for embedded coding of wavelet coefficients

Nowadays, the rate-distortion performance of distributed video coding (DVC) is not satisfied despite its distinct contribution to low-complexity encoding. This paper presents a new residual DVC using an optimized trellis coded quantization (TCQ) to improve the performance of the current schemes. H.264/AVC intra-frame coding is firstly used to obtain the referenced frame, and then the residual between Wyner-Ziv frame and the referenced frame is Wyner-Ziv encoded with a proposed optimized TCQ which consists of the improved quadtree and the improved TCQ, both considering the characters of wavelet coefficients in different sub-bands. Experimental results show that the proposed scheme outperforms the referenced in rate-distortion performance, and the goal of low-complexity encoding is achieved.

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Embedded Coding of the Motion-Compensated 3-D Wavelet Coefficients by Concatenating Spatial and Temporal Orientation Trees

2006 IEEE International Conference on Multimedia and Expo ◽

10.1109/icme.2006.262867 ◽

2006 ◽

Cited By ~ 1

Author(s):

Liang Zhang

Keyword(s):

Temporal Orientation ◽

Wavelet Coefficients ◽

Embedded Coding

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Priorization of region-of-interest (ROI) using embedded coding of wavelet coefficients

10.1117/12.327103 ◽

1998 ◽

Author(s):

Luc Martel ◽

Andre Zaccarin

Keyword(s):

Region Of Interest ◽

Wavelet Coefficients ◽

Embedded Coding

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VIDEO DENOISING BASED ON EXPLOITING INTRASCALE AND INTERSCALE DEPENDENCY IN WAVELET DOMAIN

International Journal of Computer and Communication Technology ◽

10.47893/ijcct.2017.1404 ◽

2017 ◽

pp. 82-86

Author(s):

Karabi Devi ◽

DEEPIKA HAZARIKA ◽

V. K. NATH

Keyword(s):

Time Domain ◽

Low Complexity ◽

Video Frame ◽

Discrete Wavelet ◽

Wavelet Domain ◽

Wavelet Coefficients ◽

Video Denoising ◽

Temporal Filter ◽

Spatio Temporal ◽

Temporal Direction

In this paper, we propose a new video denoising algorithm which uses an efficient wavelet based spatio-temporal filter. The filter first applies 2D discrete wavelet transform (DWT) in horizontal and vertical directions on an input noisy video frame and then applies 1-D discrete cosine transform (DCT) in the temporal direction in order to reduce the redundancies which exist among the wavelet coefficients in the temporal direction. We observe that the subband coefficients with large magnitudes occur in clusters in locations corresponding to the edge locations even after applying the above spatiotemporal filter. In this paper, we propose to use two different low complexity wavelet shrinkage based methods to denoise the noisy wavelet coefficients in different subbands. The first method exploits the intra-scale dependencies between the coefficients and thresholds the wavelet coefficients based on the measure of sum of squares of all wavelet coefficients within a square neighborhood window. The second method exploits the inter-scale dependencies between the coefficients at different scales in an individual slice of coefficients. After filtering the individual slices of coefficients, the denoised video frames in time domain are obtained after inverse transforms. We propose to exploit the temporal redundancies between the successive frames again in the time domain using low complexity selective recursive temporal filtering (SRTF). In the proposed video denoising scheme, since the temporal redundancy is exploited both in the time and wavelet domain, the denoising capability of the scheme is hence increased. The video denoising performance using the two proposed approaches outperform many existing well known video denoising techniques including one recent well known method which uses the similar transformation, both in terms of PSNR and visual quality. We also show that, simple soft thresholding using Donoho’s threshold when used with this wavelet based spatio-temporal filter even outperforms many well known non linear based video denoising techniques.

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Multispectral Image Compression Based on DSC Combined with CCSDS-IDC

The Scientific World JOURNAL ◽

10.1155/2014/738735 ◽

2014 ◽

Vol 2014 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

Jin Li ◽

Fei Xing ◽

Ting Sun ◽

Zheng You

Keyword(s):

Image Compression ◽

High Performance ◽

Image Data ◽

Low Complexity ◽

Distributed Source Coding ◽

Multispectral Image ◽

Multispectral Images ◽

Wavelet Coefficients ◽

3D Dwt ◽

Multispectral Image Compression

Remote sensing multispectral image compression encoder requires low complexity, high robust, and high performance because it usually works on the satellite where the resources, such as power, memory, and processing capacity, are limited. For multispectral images, the compression algorithms based on 3D transform (like 3D DWT, 3D DCT) are too complex to be implemented in space mission. In this paper, we proposed a compression algorithm based on distributed source coding (DSC) combined with image data compression (IDC) approach recommended by CCSDS for multispectral images, which has low complexity, high robust, and high performance. First, each band is sparsely represented by DWT to obtain wavelet coefficients. Then, the wavelet coefficients are encoded by bit plane encoder (BPE). Finally, the BPE is merged to the DSC strategy of Slepian-Wolf (SW) based on QC-LDPC by deep coupling way to remove the residual redundancy between the adjacent bands. A series of multispectral images is used to test our algorithm. Experimental results show that the proposed DSC combined with the CCSDS-IDC (DSC-CCSDS)-based algorithm has better compression performance than the traditional compression approaches.

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