Authors:
Pooneh Bagheri Zadeh
1
;
Tom Buggy
1
and
Akbar Sheikh Akbari
2
Affiliations:
1
Glasgow Caledonian University, United Kingdom
;
2
University of Bristol, United Kingdom
Keyword(s):
Discrete cosine transform, image compression, perceptual weights, statistical parameters.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Filtering
;
Image Formation and Preprocessing
;
Image Quality
;
Implementation of Image and Video Processing Systems
;
Statistical Approach
Abstract:
This paper presents a novel progressive statistical and discrete cosine transform based image-coding scheme. The proposed coding scheme divides the input image into a number of non-overlapping pixel blocks. The coefficients in each block are then decorrelated into their spatial frequencies using a discrete cosine transform. Coefficients with the same spatial frequency at different blocks are put together to generate a number of matrices, where each matrix contains coefficients of a particular spatial frequency. The matrix containing DC coefficients is losslessly coded to preserve visually important information. Matrices, which consist of high frequency coefficients, are coded using a novel statistical encoder developed in this paper. Perceptual weights are used to regulate the threshold value required in the coding process of the high frequency matrices. The coded matrices generate a number of bitstreams, which are used for progressive image transmission. The proposed coding scheme,
JPEG and JPEG2000 were applied to a number of test images. Results show that the proposed coding scheme outperforms JPEG and JPEG2000 subjectively and objectively at low compression ratios. Results also indicate that the decoded images using the proposed codec have superior subjective quality at high compression ratios compared to that of JPEG, while offering comparable results to that of JPEG2000.
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