Bilateral filter

About: Bilateral filter is a research topic. Over the lifetime, 3500 publications have been published within this topic receiving 75582 citations.

Adaptive Switching Non-local Filter for the Restoration of Salt and Pepper Impulse-Corrupted Digital Images

Abstract: The paper presents an effective nonlinear adaptive switching non-local filter for the restoration of impulse-corrupted digital images by using distinct impulse detection and correction stages. The correction scheme of the filter adaptively switches between details-preserving non-local mode and signal restoration-based local mode to facilitate high fidelity in the restored image. The non-local filtering operation replaces impulses with a remote pixel that better suits the local image conditions. The algorithm works in this non-local mode only when there are sufficient uncorrupted pixels in the local neighborhood of the corrupted pixel to be replaced. Otherwise, the algorithm replaces impulsive pixels with the median of the uncorrupted pixels from the local neighborhood. Experimental results from various impulse noise levels support the improved performance of the proposed algorithm over other algorithms both subjectively and objectively.

Blocking artifacts reduction using adaptive bilateral filtering

Abstract: In this paper, we propose a simple, non iterative blocking artifacts reduction method for block discrete cosine transform (DCT) compressed images, using adaptive bilateral filter. Bilateral filter when applied on a input image, smooths out the blocking artifacts by weighted averaging of the pixel values without smoothing the edges. The proper selection of the bilateral filter parameters is very important and affects the filtering results significantly. We select the bilateral filter parameters optimally, through empirical study. The bilateral filter parameters are made adaptive to different decompressed images using different quantization tables. Our main contribution in this paper is to select the bilateral filter parameters optimally and adaptively through empirical study, in application to image deblocking. The proposed method shows highly encouraging results both objectively and subjectively, when compared to many state of the art image deblocking schemes including a recent method based on adaptive bilateral filter.

Permutohedral Lattice CNNs

Abstract: This paper presents a convolutional layer that is able to process sparse input features. As an example, for image recognition problems this allows an efficient filtering of signals that do not lie on a dense grid (like pixel position), but of more general features (such as color values). The presented algorithm makes use of the permutohedral lattice data structure. The permutohedral lattice was introduced to efficiently implement a bilateral filter, a commonly used image processing operation. Its use allows for a generalization of the convolution type found in current (spatial) convolutional network architectures.

Mode adaptive intra prediction smoothing in video coding

Abstract: A method for decoding an encoded video bit stream in a video decoder is provided that includes decoding an intra prediction mode for a block of pixels encoded in the video bit stream, determining, based on the intra prediction mode, whether or not a smoothing filter is to be applied to reference pixel values used for intra prediction of the block, applying a smoothing filter to the reference pixel values when a result of the determining is that a smoothing filter is to be applied, and performing intra prediction according to the intra prediction mode using the smoothed reference pixel values to generate a predicted block of pixels.