Pre and Postprocessing for JPEG to Handle Large Monochrome Images

Abstract

Image compression is one of the most important fields of image processing. Because of the rapid development of image acquisition which will increase the image size, and in turn requires bigger storage space. JPEG has been considered as the most famous and applicable algorithm for image compression; however, it has shortfalls for some image types. Hence, new techniques are required to improve the quality of reconstructed images as well as to increase the compression ratio. The work in this paper introduces a scheme to enhance the JPEG algorithm. The proposed scheme is a new method which shrinks and stretches images using a smooth filter. In order to remove the blurring artifact which would be developed from shrinking and stretching the image, a hyperbolic function (tanh) is used to enhance the quality of the reconstructed image. Furthermore, the new approach achieves higher compression ratio for the same image quality, and/or better image quality for the same compression ratio than ordinary JPEG with respect to large size and more complex content images. However, it is an application for optimization to enhance the quality (PSNR and SSIM), of the reconstructed image and to reduce the size of the compressed image, especially for large size images.

A Systematic Multichimera Transform for Color Image Representation

“…Masks were designed such that they represented different patterns in images. This transform achieved superior performance than that of methods in [22,23], but its performance also deteriorated when image blocks became larger than 4 × 4. To mitigate this drawback, a multichimera transform was developed in [25].…”

“…However, converting the image into a mathematical representation requires a huge amount of work and multistep analysis. Some efforts were conducted in [22][23][24][25] to convert the image into a set of mathematical representations, which demonstrated the initial steps to achieve this goal. In [22], each image block was expressed as three coefficients using a new curve-fitting technique with a hyperbolic tangent function.…”

“…The main limitation of this method is that it can only deal with an image block of 4 × 4, and its efficiency deteriorates with larger block sizes. To solve this limitation, the hyperbolic tangent function was employed after applying the DCT in [23]. This improved the quality of the reconstructed image.…”

“…A few coefficients are estimated from each block using a precomputed codebook of size 2096 × 16 × 16. Thus, the image can be represented using a few coefficients, and a larger compression ratio can be obtained than those obtained in [22][23][24]. The disadvantage of this method is in the way in which the codebook is generated, where statistical mathematical representations and a set of images are required to construct the codebook, which complicates the whole work.…”

Chimera: A New Efficient Transform for High Quality Lossy Image Compression

“…Their results show an enhancement of up to 20 dB of PSNR. In addition, Khalaf et al shows the effects of preprocessing and postprocessing on the compressed images using DCT which address the issues of the monochrome images [14]. Lu et al extended an optimal piecewise linear approximation for images from 1D curve fitting to 2D surface fitting by a dual-agent algorithm.…”