Equalize the histograms of the given images so that they provide more perceptual information. Note that the images are in color, therefore you may have to do some extra work.
Just express your equalization algorithm briefly. Plot the histograms of one sample image (let's agree on the first sample) before and after equalization. You can plot independent histograms for R, G and B channels of your images, assuming that they are independent (random variables). Explain how you processed these color images, i.e. explain what you won't do if these images were graylevel images.
Enhance the noisy images by using point operations and/or spatial operations in set (2.1). Extract the edges of the images by spatial operations in set (2.2).
Image set 2.1
Image set 2.2
Your report should be less than three pages, with no limitation in number of figures and tables, but it must not get oversized (to make things easy, no cover pages). The reports should be either in PostScript (ps.gz and ps.Z are also OK) or PDF (preferred) formats, which means there's no need for a hardcopy. The report must include the items explained above to be complete.
Your programs has to output some image, otherwise it'll make a zero! You'll be requested a demo in case your program(s) fail to output an image. Your performance will be determined by the (of course) quality of your output and to be measured qualitatively. Three of the five test images are provided in this page; the `hidden' two others are chosen to be similar to the public ones in characteristics.
Your programs will be executed on a RedHat 6.x linux machine, one of the ineks, exactly speaking.
It seems that this assignment can be completed without tricking any of the tools you're using. If you think you need, please post your opinion to the newsgroup.
