No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Optimal quantisation of the discrete cosine transform for image compression
Abstract
We propose a method for constructing optimal quantisation tables
for use with discrete cosine transform (DCT) based image compressors.
The method produces optimal rate distortion performance when linear
quantisation and a fixed block size DCT are used. The quantisation table
for the image is transmitted as part of the compressed file. We show
that the rate distortion performance is superior to JPEG and close to
that of wavelet methods. Unlike JPEG our method is progressive and
produces the exact compression ratio required
... As a result, the optimised quantisation tables of this model have significantly improved the compression performance (fidelity) in comparison with the default JPEG quantisation tables (Monro and Sherlock, 1996). Bethel et al. (1997) proposed a method to generate an optimal JPEG quantisation table in terms of rate-distortion performance. Thus, this method has been developed to get the best possible tradeoff between high compression and low distortion. ...
... As a result, this method yielded a better rate-distortion performance than that of default JPEG compression (Bethel et al., 1997). ...
... Methods for determining the quantization table are usually based on rate-distortion theory. These methods do achieve better performance than the JPEG default quantization table [8, 9]. However, the quantization tables based on rate distortion theory methods are image-dependent and the complexity of the encoder is rather high. ...
This paper discusses lossy image compression using Hadamard Transform (HT). Quantization table plays significant role in image compression (lossy) that improves the compression ratio without sacrificing visual quality. In this work, Human Visual system (HVS) is considered to derive the quantization table, which is applicable for Hadamard Transform. By incorporating the human visual system with the uniform quantizer, a perceptual quantization table is derived. This quantization table is easy to adapt to the specified resolution for viewing. Results show that this quantization table is good in terms of improving peak signal to noise ratio (PSNR), Normalized Cross correlation (NCC) and to reduce blocking artifacts. This work is extended to test the robustness of watermarking against various attacks.
... ISO/CCITT Joint Photographic Experts Group (JPEG) has selected DCT for its baseline coding technique [2, 3]. In a block-based JPEG compression algorithm, all DCT co-efficients [4] are utilized in compressing the image. However, significant energy of the image is represented by DC co-efficient of image block. ...
In this work, an adaptive image compression algorithm is proposed based on the prediction of AC coefficients in Discrete Cosine Transform (DCT) block during reconstruction of image. In the prediction phase, DC values of the nearest neighbour DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Results show that this method is good in terms of good Peak Signal to Noise Ratio (PSNR) and less blocking artifacts. The proposed scheme has been demonstrated through several experiments including Lena. Reconstructed image is of good quality with same compression ratio compared to the existing technique in the literature. In addition, an image watermarking algorithm is proposed using DCT AC coefficients obtained. The performance of the proposed watermarking scheme is measured in terms of PSNR and Normalized Cross Correlation (NCC). Further, this algorithm is robust for various attacks including JPEG compression on watermarked image.
... Methods for determining the quantization table are usually based on rate-distortion theory. These methods do achieve better performance than the JPEG default quantization table [3,4,5]. However, the quantization tables are image-dependent and the complexity of the encoder is rather high. ...
This paper presents a new compression technique and image watermarking algorithm based onContourlet Transform (CT). For image compression, an energy based quantization is used. Scalar quantizationis explored for image watermarking. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) isused to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link pointdiscontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in apre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, thecoefficients of CT are quantized based on the energy in the particular band. The superiority of proposedalgorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared withwavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours. Thewatermark image is embedded in the low pass image of contourlet decomposition. The watermark can beextracted with minimum error. In terms of PSNR, the visual quality of the watermarked image is exceptional.The proposed algorithm is robust to many image attacks and suitable for copyright protection applications.
... ISO/CCITT Joint Photographic Experts Group (JPEG) has selected DCT for its baseline coding technique [2, 3]. In a block-based JPEG compression algorithm, all DCT co-efficients [4] are utilized in compressing the image. However, significant energy of the image is represented by DC co-efficient of image block. ...
In this work, an adaptive image compression algorithm is proposed based on the prediction of AC coefficients in Discrete Cosine Transform (DCT) block during reconstruction of image. In the prediction phase, DC values of the nearest neighbour DCT blocks is utilized to predict the AC coefficients of centre block. Surrounding DC values of a DCT blocks are adaptively weighed for AC coefficients prediction. Linear programming is used to calculate the weights with respect to the image content. Results show that this method is good in terms of good Peak Signal to Noise Ratio (PSNR) and less blocking artifacts. The proposed scheme has been demonstrated through several experiments including Lena. Reconstructed image is of good quality with same compression ratio compared to the existing technique in the literature. In addition, an image watermarking algorithm is proposed using DCT AC coefficients obtained. The performance of the proposed watermarking scheme is measured in terms of PSNR and Normalized Cross Correlation (NCC). Further, this algorithm is robust for various attacks including JPEG compression on watermarked image.
We present a novel method for sparse signal recovery using Particle Swarm Optimization and demonstrate an application in image compression. Images are compressed with compressive sampling, and then reconstructed with particle swarm techniques. Several enhancements to the basic particle swarm algorithm are shown to improve signal recovery accuracy. We also present techniques specifically for re-constructing sparse image data and evaluate their performance.
This paper presents a new compression technique based on Contourlet Transform (CT) and energy based quantization. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) is used to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link point discontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in a pre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, the coefficients of CT are quantized based on the energy in the particular band. The superiority of proposed algorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared with wavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours.
ResearchGate has not been able to resolve any references for this publication.