Fuzzy-set and directional image processing techniques for impulsive noise reduction employing DSP

In literature, numerous algorithms in image denoising in case of a noise of different nature were implemented. One of the principal noises is impulsive one companioning any transmission process. This paper presents novel approach unificating two most powerful techniques used during last years: directional processing and fuzzy-set techniques. Novel method permits the detection of noisy pixels and local movements (edges and fine details) in a static image or in an image sequence. The proposed algorithm realizes the noise suppression preserving fine details and edges, as so as color chromaticity properties in the multichannel image. We present applications of proposed algorithm in color imaging and in multichannel remote sensing from several bands. Finally, hardware requirements are evaluated permitting real time implementation on DSP of Texas Instruments using a Reference Framework defined as RF5. It was implemented on DSP the multichannel algorithms in a multitask process that permits to improve the performance of several tasks, and at the same time enhancing the time processing and reducing computational charge in a dedicated hardware. Numerous experimental results in the processing the color images/sequences and satellite remote sensing data show the superiority of proposed approach as in objective criteria (PSNR, MAE, NCD), as in visual subjective way. The needed processing times and visual characteristics are exposed in the paper demonstrating accepted performance of the approach.