JOURNAL ARTICLE

Survey Paper on Fractal Image Compression using Block Truncation Coding Technique

Anshu AgrawalPushpraj Singh

Year: 2018 Journal:   International Journal of Computer Applications Vol: 182 (3)Pages: 19-22

Abstract

Text and image data are important elements for information processing almost in all the computer applications.Uncompressed image or text data require high transmission bandwidth and significant storage capacity.Designing an efficient compression scheme is more critical with the recent growth of computer applications.Modern applications, in addition to high compression ratio, also demand for efficient encoding and decoding processes, so that computational constraint of many real-time applications is satisfied.Two generally utilized spatial area pressure strategies are block truncation coding (BTC) and vector quantization (VQ).BTC strategy brings about great quality picture with high piece rate, while the VQ is notable for low piece rate yet creates low quality pictures.In further work of this paper is multi-level BTC includes BTC algorithm as well as vector quantization method for purpose of multi-leveltechnique for gray and color image.

Keywords:
Computer science Fractal compression Block Truncation Coding Coding (social sciences) Truncation (statistics) Image compression Fractal Block (permutation group theory) Data compression Image (mathematics) Algorithm Artificial intelligence Image processing Statistics Machine learning Mathematics

Metrics

1
Cited By
0.14
FWCI (Field Weighted Citation Impact)
10
Refs
0.43
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Chaos-based Image/Signal Encryption
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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