Open AccessAnalysing JPEG Coding With Masking
Author(s) -
Si Yong Yeo,
Yok-Yen Nguwi
Publication year - 2016
Publication title -
international journal of multimedia and its applications
Language(s) - English
Resource type - Journals
eISSN - 0975-5934
pISSN - 0975-5578
DOI - 10.5121/ijma.2016.8104
Subject(s) - masking (illustration) , computer science , coding (social sciences) , jpeg , jpeg 2000 , artificial intelligence , data compression , art , mathematics , image compression , image processing , statistics , visual arts , image (mathematics)
The growing trend of online image sharing and downloads today mandate the need for better encoding and decoding scheme. This paper looks into this issue of image coding. Multiple Description Coding is an encoding and decoding scheme that is specially designed in providing more error resilience for data transmission. The main issue of Multiple Description Coding is the lossy transmission channels. This work attempts to address the issue of re-constructing high quality image with the use of just one descriptor rather than the conventional descriptor. This work compare the use of Type I quantizer and Type II quantizer. We propose and compare 4 coders by examining the quality of re-constructed images. The 4 coders are namely JPEG HH (Horizontal Pixel Interleaving with Huffman Coding) model, JPEG HA (Horizontal Pixel Interleaving with Arithmetic Encoding) model, JPEG VH (Vertical Pixel Interleaving with Huffman Encoding) model, and JPEG VA (Vertical Pixel Interleaving with Arithmetic Encoding) model. The findings suggest that the use of horizontal and vertical pixel interleavings do not affect the results much. Whereas the choice of quantizer greatly affect its performance