Tuning of Fuzzy Sharpening Filters for Biomedical Image Enhancement

Color image enhancement based on perceptual sharpening

In this paper we present a sharpening operator for color images that is based on perceptual considerations about how human visual behaves for color scenes. Color contrast is an induction phenomenon of the visual system that varies the chromaticity of a color region depending on the color of its surround, provoking an enhanced perception of color scenes. This effect can be simulated by a sharpen...

Fuzzy Techniques for Image Enhancement

The aim of image enhancement is to improve the interpretability or perception of information in images for human viewers, or to provide 'better' input for other automated image processing techniques. Fuzzy techniques can manage the vagueness and ambiguity efficiently (an image can be represented as fuzzy set). Fuzzy logic is a powerful tool to represent and process human knowledge in form of fu...

Guided Filters for Depth Image Enhancement

Adjustable Quadratic Filters for Image Enhancement

We propose a new class of mapping-based nonlinear quadratic Volterra filters for image enhancement. The input signal is mapped prior to filtering by a memoryless one-to-one nonlinear mapping function. The mapping function can be described by any arbitrary function and implemented by a simple look-up table. If necessary, an inverse mapping function is applied after filtering. Using this general ...

Fuzzy adaptive filters for multichannel image processing

New filter classes for multichannel image processing are introduced and analyzed. The proposed methodology constitutes a unifying and powerful framework for multichannel image processing. The new filters use fuzzy membership functions based on different distance measures among the image vectors to adapt to local data in the image. The principle behind the new nonlinear filters is explained in d...