Title :
Gray and color image contrast enhancement by the curvelet transform
Author :
Starck, Jean-Luc ; Murtagh, Fionn ; Candès, Emmanuel J. ; Donoho, David L.
Author_Institution :
Commissariat a l´´Energie Atomique-Saclay, Gif sur Yvette, France
fDate :
6/1/2003 12:00:00 AM
Abstract :
We present a new method for contrast enhancement based on the curvelet transform. The curvelet transform represents edges better than wavelets, and is therefore well-suited for multiscale edge enhancement. We compare this approach with enhancement based on the wavelet transform, and the multiscale retinex. In a range of examples, we use edge detection and segmentation, among other processing applications, to provide for quantitative comparative evaluation. Our findings are that curvelet based enhancement out-performs other enhancement methods on noisy images, but on noiseless or near noiseless images curvelet based enhancement is not remarkably better than wavelet based enhancement.
Keywords :
edge detection; image colour analysis; image enhancement; image segmentation; noise; transforms; color image contrast enhancement; curvelet transform; edge detection; gray image contrast enhancement; image segmentation; mulfiscale edge enhancement; multiscale retinex; near noiseless images; noiseless images; noisy images; quantitative comparative evaluation; wavelet based enhancement; Color; Computer vision; Displays; Dynamic range; Histograms; Image coding; Image edge detection; Image segmentation; Laplace equations; Wavelet transforms;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2003.813140