Adaptive Bilateral Filter for Sharpness Enhancement and Noise Removal

Abstract

In this paper, we present the adaptive bilateral filter (ABF) for sharpness enhancement and noise removal. The ABF sharpens an image by increasing the slope of the edges without producing overshoot or undershoot. It is an approach to sharpness enhancement that is fundamentally different from the unsharp mask (USM). This new approach to slope restoration also differs significantly from previous slope restoration algorithms in that the ABF does not involve detection of edges or their orientation, or extraction of edge profiles. In the ABF, the edge slope is enhanced by transforming the histogram via a range filter with adaptive offset and width. The ABF is able to smooth the noise, while enhancing edges and textures in the image. The parameters of the ABF are optimized with a training procedure. ABF restored images are significantly sharper than those restored by the bilateral filter. Compared with an USM based sharpening method-the optimal unsharp mask (OUM), ABF restored edges are as sharp as those rendered by the OUM, but without the halo artifacts that appear in the OUM restored image. In terms of noise removal, ABF also outperforms the bilateral filter and the OUM. We demonstrate that ABF works well for both natural images and text images.

Pixel-wise decay parameter adaption for nonlocal means image denoising

“…(4) and utilize the noise componentñ estimated using the method noise to approximate n for var½μðx; yÞ in Eq. (5). After estimating the two components in EfMSE½μðx; yÞg, a cost function of EfMSE½μðx; yÞg with respect to hðx; yÞ will be established.…”

“…Numerous denoising methods have been proposed, such as the spatial adaptive methods, 1 the partial differential equations-based methods, 2,3 the wavelet-based methods, 4 and bilateral filtering methods. 5 All these methods are based on the so-called locally adaptive recovery paradigm. Recently, the nonlocal means (NLM) method 6 has attracted much attention in the field of image denoising, due to its better restoration performance than the above-mentioned locally adaptive methods.…”

Adaptive noise-reducing anisotropic diffusion filter

“…The essential link between bilateral filtering and anisotropic diffusion is examined in [22]. In more recent years, adaptive bilateral filters are proposed in [23][24][25]. These filters retain the general form of the bilateral filter, but differ when introducing an offset in the range of the filter.…”

Performance of bilateral filtering on Gaussian noise

“…(10). Thus, we assume that E t ½R m 0 ;n 0 is statistically independent of the numerator term in Eq.…”

“…Bilateral filter research can be divided into four areas: theoretical study, 4-6 determination of optimal parameters, [7][8][9] improvement of image quality, 10,11 and speed up. 12,13 Bilateral filtering can be related to well-known techniques: Elad 4 derived the bilateral filter from statistical estimation and regularization theories and showed that the bilateral filter was equivalent to a single iteration of the diagonal-normalized steepest descent.…”