In this article, we propose a new class of multichannel filters, vector rank M-type K-nearest neighbor (VRMKNNF) filters that can obtain the balance between noise suppression, and edge and fine detail preservation, especially in color image restoration. The proposed VRMKNNF filters are mainly based on the combined RM-estimators with different influence functions. An adaptive non parametric approach that determines the functional form of the density probability of noise from data into the sliding filtering window has been employed to improve the performance of the multichannel filters. Applying the VRMKNNF as a reference filter we designed the adaptive multichannel non parametric VRMKNNF (AMN-VRMKNNF). Numerous simulations presented in the article illustrate that the VRMKNNF and AMN-VRMKNNF filters exhibit the robust and adaptive capability in multichannel imaging applications. Finally, we present the implementation of proposed filters on the DSP TMS320C6711 demonstrating that they can potentially provide a real-time solution to quality video transmission. ©2005, IS&T - The Society for Imaging Science and Technology.
|Original language||American English|
|Number of pages||183|
|Journal||Journal of Imaging Science and Technology|
|State||Published - 1 May 2005|