Bilateral filter

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

Three-dimensional median and recursive filtering apparatus and method for video image enhancement

Abstract: According to a presently preferred embodiment of the invention, image enhancement apparatus for digital video images comprises a two-stage filter comprising a median filter and a recursive filter The median filter operates in one, two, and three dimensions wherein the cluster of pixels framing the center pixel are ranked, and the median value of the pixel cluster is chosen as the correct pixel value The pixel cluster configuration is selectable, as are the planes where the pixels are located Multiple weights may be given to the appropriate median filter inputs A motion detector is used to prevent replacement of each pixel by its pixel cluster median value when there is excessive motion Finally an adjustable pixel-replacement threshold is defined Each pixel must deviate from its median value before it is replaced by that value In the presence of rapid motion in the picture, the operation of the median filter is reduced or halted by a properly derived motion signal according to the present invention, thus preventing motion artifacts from occurring

A General Framework for Bilateral and Mean Shift Filtering.

Abstract: We present a generalization of the bilateral filter that can be applied to feature-preserving smoothing of signals on images, meshes, and other domains within a single unified framework. Our discretization is competitive with state-of-the-art smoothing techniques in terms of both accuracy and speed, is easy to implement, and has parameters that are straightforward to understand. Unlike previous bilateral filters developed for meshes and other irregular domains, our construction reduces exactly to the image bilateral on rectangular domains and comes with a rigorous foundation in both the smooth and discrete settings. These guarantees allow us to construct unconditionally convergent mean-shift schemes that handle a variety of extremely noisy signals. We also apply our framework to geometric edge-preserving effects like feature enhancement and show how it is related to local histogram techniques.

Sparse readout method and apparatus for a pixel array

Abstract: Information is obtained from the pixels of a spatial pixel array, such as a sub-atomic particle detector array, by discriminating between pixels that have and have not received actuating inputs, and obtaining outputs only from selected pixels. These pixels are determined by the pixels which have received actuating inputs, and may consist of the hit pixels and their immediate neighbors. The system monitors for the occurrence of an event of interest that occurs over time substantially less frequently than the rate at which actuating inputs are supplied to the pixel array, and obtains outputs from the selected pixels only for the times that correspond to the occurrence of an event of interest. The amount of data to be processed is thus substantially reduced.

Automatic adaptive anisotropic digital filtering and biasing of digitized images

Abstract: Adaptive anisotropic digital filtering is automatically applied to the graycale values of substantially of all the pixels in at least a portion of a digital image by, for each such pixel, selecting and angularly orienting the matrix of coefficients of an anisotropic filter kernel as a weighting function of the gray scale values of pixels in eight, 45 degree sectors under the kernel, and then performing a convolution of the gray scale values of pixels under the kernel with the rotated kernel to generate a filtered value for the center pixel. Local brightness of the image is adjusted either in conjunction with anisotropic filtering or separately by comparing for each pixel the average gray scale value of the pixels under the kernel with a reference value and applying a bias function to the center pixel grey scale value to brighten or darken the image dependent upon the results of the comparison.

A 2D-to-3D conversion system using edge information

Abstract: The three-dimensional (3D) displays provide a dramatic improvement of visual quality than the 2D displays do. However, for existed 2D contents, depth information is not recorded. Therefore, 2D-to-3D conversion is necessary. This paper presents an automatic system which convert 2D videos to 3D videos. The proposed system groups the blocks into regions using edge information. A prior hypothesis of depth gradient is used to assign depth of regions. Then, the bilateral filter is also applied to diminish block effect and to generate comfortable depth map for 3D visualization.