Matlab code for JPEG2000 Image Compression Standard.

As digital imagery becomes more commonplace and of higher quality, there is a need to manipulate more and more data. Thus, image compression must not only reduce the necessary storage and bandwidth requirements, but also allow extraction for editing, processing, and targeting particular devices and applications. The JPEG-2000 image compression system has a rate-distortion advantage over the original JPEG. More importantly, it also allows the extraction of different resolutions, pixel fidelities, regions of interest, components, and more, all from a single compressed bit-stream. This allows an application to manipulate or transmit only the essential information for any target device from any JPEG 2000 compressed source image.

MATLAB code of Image Negation and Image Enhancement using Histogram Equilization.

Image Negation:

The negative point transformation function also known as contrast reverse. The negative transformation is used to make the output more suitable for the task at hand (e.g., by making it easier to notice interesting details in the image).

Where‘s’ is Output image after transformation

L-1 is Maximum Pixel value

r is Input Image.