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Test images

Images used in [Portilla 2003b]:


Lena Barbara Boat
Fingerprint House Peppers


zip All of them 926.83 Kb .


Five of the images (commonly known as Lena, Barbara, Boats, House and Peppers) are widely used in the image processing literature. Unfortunately, most test images are available in more than one version, with differences between them due to cropping, scanning, resizing, compression or conversion from color to gray-level. In the versions used in this paper the first three are 512 x 512 and the last two are 256 x 256. We also included a 512 x 512 image of a fingerprint, which unlike the other images, is a homogeneous texture.

Among the several versions of 512 x 512 8-bit gray-level Lena, we chose the one that seems the most standard from Mike Wakin's web page. For the comparison of Fig. 5 of our paper, Dr. Starck [1] generously offered to run his algorithm on our test image, and Dr. Li [2] and Dr. Sendur [3] kindly confirmed they were using the same version of the image. The Barbara image was obtained from Marco Schmidt's standard test images database. This version had been previously used in [2] where, in turn, there is a comparison to [4]. It has also been used in [3]. The Boats image was taken from SIPI image database (University of Southern California). This same version has been used in [3]. The House and Peppers images were kindly provided by Dr. Pizurica for proper comparison to her results reported in [5].

[1] J L Starck, D L Donoho, and E Candes. "Very high quality image restoration", in Proc. SPIE Conf. Signal and Image Processing. San Diego, August 2001, vol. 4478, pp. 9-19. A Laine, M Unser and A Aldroubi. Eds.
[2] X Li and M T Orchard. "Spatially adaptive image denoising under overcomplete expansion", in IEEE Int'l Conf on Image Proc. Vancouver, September 2000.
[3] L Sendur and I W Selesnick. "Bivariate shrinkage with local variance estimation", IEEE Signal Processing Letters, vol. 9, no. 12, pp. 438-441. December 2002.
[4] S G Chang, B Yu, and M Vetterli. "Spatially adaptive wavelet thresholding with context modeling for image denoising", in 5th IEEE Int'l Conf. on Image Proc., Chicago, October 1998.
[5] A Pizurica, W Philips, I Lemahieu, and M Acheroy. "A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising", IEEE Trans. Image Proc., vol, 11, no. 5, pp. 545-557, May 2002.