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Abstract-New adaptive filters for color image processing are introduced and analyzed in this paper. The proposed adaptive methodology constitutes a unifying and powerful framework for multichannel signal processing. Using the proposed methodology, color image filtering problems are treated from a global viewpoint that readily yields and unifies previous, seemingly unrelated, results. The new filters utilize Bayesian techniques and nonparametric methodologies to adapt to local data in the color image. The principles behind the new filters are explained in detail. Simulation studies indicate that the new filters are computationally attractive and have excellent performance.

A new class of filters for multichannel image processing is introduced and analyzed in this brief. This class constitutes a generalization of vector directional filters. The proposed filters use fuzzy transformations of the angles among the different vectors to adapt to local data in the image. The principle behind the new filters is explained and comparisons with other popular nonlinear filters are provided. The specific case of color image processing is studied as an important example of multichannel image processing. Simulation results indicate that the new filters offer some flexibility and have excellent performance.

Color is the characteristic which is most used for image indexing and retrieval. Due to its simplicity, the color histogram remains the most commonly used method for this task. However, the lack of good perceptual histogram similarity measures, the global color content of histograms, and the erroneous retrieval results due to gamma nonlinearity, call for improved methods. We present a new scheme which implements a recursive HSV-space segmentation technique to identify perceptually prominent color areas. The average color vector of these extracted areas are then used to build the image indices, requiring very little storage. Our retrieval is performed by implementing a combination distance measure, based on the vector angle between two vectors. Our system provides accurate retrieval results and high retrieval rate. It allows for queries based on single or multiple colors and, in addition, it allows for certain colors to be excluded in the query. This flexibility is due to our distance measure and the multidimensional query space in which the retrieval ranking of the database images is determined. Furthermore, our scheme proves to be very resistant to gamma nonlinearity providing robust retrieval results for a wide range of gamma nonlinearity values, which proves to be of great importance since, in general, the image acquisition source is unknown.