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Impulse noise reduction or removal is a very active research area of image processing. A nonlinear hybrid filter for removing fixed impulse noise (salt & pepper) noise from color images has been proposed in this study. Technique is based on mathematical morphology and trimmed standard median filter. Proposed filter is composed of a sequence of morphological standard and well known operations erosion-dilation and trimmed standard median filter. It removes the fixed impulse noise (salt & pepper) very well without distorting the image features, color components and edges. It does not introduce blurring and moving effects even in high noise densities (up to 90%). The standard similarity measure peak signal to noise ratio (PSNR) and computation time have been used to evaluate the performance of proposed hybrid filter.

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Face recognition is one of a complex biometrics in the field of pattern recognition due to the constraints imposed by variation in the appearance of facial images. These changes in appearance are affected by variation in illumination, expression or occlusions etc. Illumination can be considered a complex problem in both indoor and outdoor pattern matching. Literature studies have revealed that two problems of textural based illumination handling in face recognition seem to be very common. Firstly, textural values are changed during illumination normalization due to increase in the contrast that changes the original pixels of face. Secondly, it minimizes the distance between interclasses which increases the false acceptance rates. This paper addresses these issues and proposes a robust algorithm that overcomes these limitations. The limitations are resolved through transforming pixels from nonillumination side to illuminated side. It has been revealed that proposed algorithm produced better results as compared to existing related algorithms.

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