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The reduction of the correlation between color channels in the color space is expected for most image compression schemes.
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Nowadays, the JPEG is the most used image compression algorithm, mainly because of its relatively easy implementation and of its fair compromise between complexity and compressed image quality.
JPEG is the most commonly used image compression standard.
Vector quantization has become one of the most popular lossy image compression techniques due to its simplicity and capability to achieve high compression ratios [10, 11].
Software implementation costs of most algorithms, designed for image compression in wireless sensor networks, do not justify their use to reduce the energy consumption and delay transmission of images.
The most common form of image compression is JPG.
Experimental results, compared with the related existing methods, show that the proposed color image scheme has stronger robustness against most common attacks such as image compression, filtering, cropping, noise adding, blurring, scaling and sharpening etc.
The discrete cosine transform (DCT) which is the most widely used technique for image compression was initially defined in [1].
In most cases, image enhancement performed after image compression tends to bring out the artifacts injected into the data due to the compression.
As one of the most frequently used transforms in digital image compression, the DCT may significantly reduce the number of design variables in density-based topology optimization, and can hereby improve the efficiency of solving the topology optimization problems to a great extent.
Among the most serious attacks is the attack by image compression such as JPEG 2000.
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