Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : image compression


Color Image Compression Using DPCM with DCT, DWT and Quadtree Coding Scheme

Ashwaq T. Hashim; Suhad A. Ali

Engineering and Technology Journal, 2016, Volume 34, Issue 4, Pages 585-597

This paper is concerned with the design and implementation of a compression method for color image. This method based on Differential Pulse Code Modulation (DPCM), Discrete Cosine Transform (DCT) , Discrete Wavelet Transform (DWT) and Quadtree Coding Scheme. As a first step the DPCM technique is used to isolate blocks of an image into correlated and uncorrelated blocks. The isolated correlated blocks have been compressed using DCT based compression method then each block has been embedded with zeros on the original image. Each uncorrelated block has been compressed using DWT based method and put the compressed block in its location on the original image. Then, the result (i.e., the zeros blocks and compressed blocks with DWT) coded using Quadtree spatial coding. The output from DWT based and DCT based passed through shift coding stage to gain a possible further compression. The performance results of proposed hybrid algorithms produces better quality of image in terms of Peak-Signal-to-Noise Ratio (PSNR) with a higher Compression Ratio (CR) compared to standalone DCT or DWT. The PSNR values of the reconstructed images after applying proposed system are ranged from 30.62 to 40.95dB and CR on average, have been reduced to be around 1:19.6 of the size of the original image.

Ear Recognition by Using Self Organizing Feature Map

Suad K. Mohammad

Engineering and Technology Journal, 2013, Volume 31, Issue 10, Pages 2000-2013

A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.
The aim of the work presented within this paper is to develop an optimum image compression system using haar wavelet transform and a neural network. In this paper we have developed and illustrated a recognition system for human ears using a Kohonen self-organizing map (SOM) or Self-Organizing Feature Map (SOFM) based retrieval system. SOM has good feature extracting property due to its topological ordering. The ear Analytics results for the 4 images of database reflect that the ear recognition using one of the neural network algorithms SOM for 4 persons. MATLAB programs were used to complete this work.

Image Compression Using Lifting Scheme

Yasir A. Ahmed Al-Obaidi; Hadeel N. Abdullah

Engineering and Technology Journal, 2010, Volume 28, Issue 17, Pages 5455-5467

This paper introduces, firstly, a proposed method of computing one and
two-dimensional wavelet transform .The proposed method reduces heavily
processing time for decomposition of image keeping or overcoming the quality of
reconstructed images. Also, the inverse procedures of all the transformations for
multi- dimensional cases verified.
Secondly, computes quantization and run length encoder. Different types
of quantization are presented in this paper with effects of these differences on
Compression Ratio (CR).
Thirdly, compute PSNR, RMSE, CR, and size. The effect noted this
difference in levels of FLWT on same picture, where PSNR, MSRE, SIZE, and
CR different from one level to another.

Image Compression Based on 2D Dual Tree Complex Wavelet Transform (2D DT-CWT)

Salih Husain Ali; Aymen Dawood Salman

Engineering and Technology Journal, 2010, Volume 28, Issue 7, Pages 1290-1305

By removing the redundant data, the image can be represented in a smaller
number of bits and hence can be compressed. There are many different methods of
image compression. This paper investigates a proposed form of compression based on
2D Dual Tree complex wavelet transform (2D DT-CWT). Many wavelet coefficients
are closed to zero. Thresholding can modify the coefficients to produce more zeros
that are allowed a higher compression rate. The wavelet analysis does not actually
compress a signal. Therefore Huffman coding is used with a signal processed by the
wavelet analysis in order to compress data. Wide range of threshold values is used in
the proposed form. From the results the proposed form give higher rate of
compression and lower RMS error compared with that forms based on Discrete
Wavelet Transform (DWT), Dual Tree Real Wavelet Transform (DT-RWT) and the
well known method based Discrete Cosine Transform (DCT).