Blocky artifacts detection algorithm for compressed digital image
Image compression is a very important issue for many applications in the field of visual communications. The purpose of image compression is to reduce the storage and transmission costs while maintaining the image quality. Nowadays, image previewing on a mobile device is a practice that takes a grea...
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| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6534/ http://eprints.uthm.edu.my/6534/1/200.pdf |
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| Summary: | Image compression is a very important issue for many applications in the field of visual
communications. The purpose of image compression is to reduce the storage and transmission costs
while maintaining the image quality. Nowadays, image previewing on a mobile device is a practice
that takes a great implementation of everyday live. However, the image compression with very low
bit rates that is typically used on mobile platforms, usually may introduce visible compression
artifacts, which is referred to blocky artifacts. This displaced blocky artifacts, although visually
noticeable and annoying, is particularly difficult for automated detection because its location is a
priori unknown, and its appearance might be easily mistaken for some real edges or fine details in
the image. Therefore, the detection of the blocky artifacts is important to ensure the deblocking
process is performed on the blocky artifacts only, not on real edges or fine details of the image. This
paper proposes the development of a technique which aims in blocky artifacts detection for
compressed digital image. The detection of blocky artifacts presented in this paper is performed in
two parts that are vertical and horizontal detections utilizing proposed detection algorithms. The
effectiveness of to detect the blocky artifacts detection without including the image edges and fine
details is depending on the threshold value setting in the vertical and horizontal detections
algorithms. After both detections are completed, then the last step is to combine both edgemaps into
a new image which includes the blocky artifacts at the boundary between two different luminance
gradients. The algorithm is developed in MATLAB software. The analysis for the result is made
based on qualitative observation. For blocky artifacts detection, the proposed technique has
achieved its objectives in detecting blocky artifact at the boundary between two different luminance
gradients. Thresholding process separated the unwanted image fine details and edges, providing an
output image a view of clearer blocky artifacts existing in the compressed image. It is also found
that the proposed technique could detect blocky artifacts more effectively (without including image
fine details and edges) in comparison to conventional techniques |
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