Abstract
The interest in coding was very high because it is widely relied on in the security of correspondence and in the security of information in addition to the need to rely on it in the storage of data because it leads to a pressure in the volume of information when storing it. In this research, image transformation was used to encode gray or color images by adopting parameters elected from contourlet transformations for image. The color images are acquired into the algorithm, to be converted into three slices (the main colors of the image), to be disassembled into their coefficients through contourlet transformations and then some high frequencies in addition to the low frequency are elected in order to reconstruct the image again. The election of low frequencies with a small portion of the high frequencies has led to bury some unnecessary information from the image components. The performance efficiency of the proposed method was measured by MSE and PSNR criteria to see the extent of the discrepancy between the original image and the recovered image when adopting different degrees of disassembly level, in addition, the extent to which the image type affects the performance efficiency of the approved method has been studied. When the practical application of the method show that the level of disassembly is directly proportional to the amount of the error square MSE and also has a great effect on the extent of correlation where the recovered image away from the original image in direct proportional with the increased degree of disassembly of the image. It also shows the extent to which it is affected by the image of different types and varieties, where was the highest value of the PSNR (58.0393) in the natural images and the less valuable in x-ray images (56.9295) as shown in table 4.
Highlights
In the past, the image compression has been used widespread in the digital image processing and it is still representing an important field for dealing with images
The results show that the proposed method preserves the images from deformation by canceling some of the image frequencies and eliminates the repeated data in images via coding technology depending on contourlet transform, it is more effective when applied it on Grayscale images and type of the natural and highdensity images
Ratio (PSNR), Mean Square Error (MSE), and Signal to Noise Ratio (SNR) for the proposed method justification, which are shown in tables
Summary
The image compression has been used widespread in the digital image processing and it is still representing an important field for dealing with images. Image compression can be used to represent the image with minimum number of bits, where it used to eliminate or reduce a redundancy and unimportant information in the image reduce storage area and increases the efficiency of the transfer [1]. Many algorithms appeared and started to grow and develop to achieve the best result of image compression. Each algorithm accomplishes its idea in a different way and in addition the image size affects the compression ratio, maybe designed for special type of images (such as medical or Aerial images) but not suitable for other types. Compression techniques have many advantages, where compression eliminate or reduce a redundancy. Alsaif information in the image, reduces the probability of transmission errors and overall execution time and provides safety against unauthorized monitoring [2]
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