Fuzzy edge detector based adaptive quantization image coding: FuzzAQC

Author

Gambhir, Deepak ; Rajpal, Navin

Author_Institution

Univ. Sch. of Inf. Technol., GGS Inderprastha Univ., Dwarka, India

fYear

2012

fDate

15-17 March 2012

Firstpage

101

Lastpage

106

Abstract

The new design method of an fuzzy edge detector based adaptive quantization image coding (fuzzAQC) is proposed. In this design first the image is decomposed to blocks and each block is AQC compressed according to their fuzzy classification as either edge or smooth blocks. This classification depends on Entropy Optimized Histogram based fuzzy edge detector. The block is coded with Bit plane, Quantization step and Block min or Block Mean. The experimental results shows that the proposed fuzzAQC scheme is superior to conventional AQC and Intensity based AQC on objective measures like MSE PSNR along with visual quality.

Keywords

data compression; edge detection; entropy; fuzzy set theory; image classification; image coding; quantisation (signal); adaptive quantization image coding; bit plane; block coding; block mean; block min; edge blocks; entropy optimized histogram; fuzzy classification; fuzzy edge detector; image compression; quantization step; smooth blocks; Educational institutions; Image coding; Image edge detection; Image reconstruction; Information technology; PSNR; Quantization; Edge Detection; Image Compression; fuzzy logic;

fLanguage

English

Publisher

ieee

Conference_Titel

Recent Advances in Information Technology (RAIT), 2012 1st International Conference on

Conference_Location

Dhanbad

Print_ISBN

978-1-4577-0694-3

Type

conf

DOI

10.1109/RAIT.2012.6194488

Filename

6194488