There are numerous fields of applications that demand the storage of large quantities of data that represent images. Many of these applications need to preserve every single detail of the input picture (e.g. medical purposes) thus image compression is necessary to reduce the number of bytes that are stored in a magnetic or optical medium. In this paper a novel method is presented that, for the first time, combines fuzzy logic principles, accomplishing smart smoothing of an image, with standard lossless compression techniques. The output of the fuzzy non-linear filtering process feeds the Q-Coder as described in JPEG standard achieving an increase of the compression ratio. Since the proposed selective smoothing of the image does not affect regions with edges or isolated points, all essential details are preserved resulting to a high quality near-lossless compression.<<ETX>>
[1]
Mark Nelson,et al.
The data compression book : featuring fast, efficient data compression techniques in C
,
1991
.
[2]
Anil K. Jain.
Fundamentals of Digital Image Processing
,
2018,
Control of Color Imaging Systems.
[3]
Glen G. Langdon,et al.
An Overview of the Basic Principles of the Q-Coder Adaptive Binary Arithmetic Coder
,
1988,
IBM J. Res. Dev..
[4]
Ronald Arps,et al.
A Multi-Purpose VLSI Chip for Adaptive Data Compression of Bilevel Images
,
1988,
IBM J. Res. Dev..
[5]
Joan L. Mitchell,et al.
Probability Estimation for the Q-Coder
,
1988,
IBM J. Res. Dev..