Showing papers on "Bilateral filter published in 1994"

Two dimensional digital hysteresis filter for smoothing digital images

Abstract: A smoothing technique for processing digital images is presented. The smoothing technique of this invention comprises a two-dimensional digital hysteresis filter which utilizes a "two-dimensional automatically adjusting variable mask" for intensity processing. As a result, the filter is independent of the image size and content and cannot alter the size of any significant intensity features, even if they are as small as one pixel in size. The intensity processing technique provides the basis for a separation of the image information into basic information groups. The two-dimensional hysteresis smoothing technique of this invention calculates the intensity value of smoothed pixels using a set of one-dimensional hysteresis lines at various angles running through each pixel in an image. Each one-dimensional hysteresis line calculates a new intensity value for each pixel in an image. These one-dimensional hysteresis values are added together and divided by the number of hysteresis lines to get the output values for the pixel. This operation requires complex processing and is preferably realized through a massively parallel processing array processor which allows near-real time processing speeds on 1K×1K images.

Visual presentation system which determines length of time to present each slide or transparency

Abstract: A system determines display durations of each of a plurality of images in a presentation based on a respective amount of the information content in the image, the greater the information content the longer the display time. There are various techniques for determining the information content of each of the images. For example, the system determines for each image the number of pixels at each of a multiplicity of respective pixel levels and the total number of pixels at one or more pixel levels for which the respective number(s) of pixels are significantly larger than the numbers of pixels at the other pixel levels. The pixels represented by these one or more pixel levels likely represent background or other mundane information. Consequently, only the pixels at the other values are considered as containing important information and their total number represents the total information content of the image. Another technique is to count the number of alphanumeric characters in an alphanumeric image as a measure of the information content in the image. A third technique is to digitially compress the image and compare the size of the compressed image to the size of the uncompressed image as a measure of the information content.

Systolic realization of motion compensated interpolation filter

Abstract: A motion compensated interpolation filter calculates an interpolated frame between two input frames of video signals having moving objects therein. The interpolation filter includes two 2-dimensional filter which are identical in structure. Each of the 2-dimensional filters has a 2-dimensional systolic array structure for providing a weighted sum of 4 pixels of each of the input frames, respectively. Each of the 2-dimensional filter includes (2N+1)·(2N+1) identical processing elements, and each of a block of (2N+1)·(2N+1) pixels is inputted to each of the processing elements, and each of the processing elements generates filter coefficients, to be multiplied to a corresponding pixel values. Since the systolic array structure inherently incorporates modularity and regularity therein, the interpolation filter is suitable for real-time processing with easy hardware implementation.

Pixel density converter

Abstract: Each one of three different, separate pixel density converters, which are alternative embodiments, operates upon an electrical signal representing successive pixels of an image. The first pixel density signal converter repeats an integration process by adding together multi-valued data representing intensity levels of two adjacent pixels, dividing by two, then repeating for such already integrated pixels to integrate a fixed number of pixels into one pixel, converting the result to a binary signal, the conversion comprising comparing the represented pixel intensity value to a fixed threshold value, and then transmitting a succession of such signals representing a plurality of adjacent data-reduced pixels. The second pixel density converter achieves comparable data reduction in a transmitted signal upon a basis of adding together a fixed number of pixels, more than two, dividing by the fixed number and performing a similar binary conversion. The third pixel density converter is similar to the second except that the fixed number is changed to satisfy the condition that the total of such numbers in a given sequence reaches a required value, the binary conversion successively yielding values upon which a resultant data-reduced signal is based, with the result that an image reproduced from the resultant signal will have reduced moire effect, which can be caused by interference between its pixels.

A cluster merging filter for noise smoothing

Abstract: Due to the statistical nature of X-rays and the electromagnetic field, medical images produced by these energy sources are contaminated with random noise, which degrades the image quality. Because of this effect, considerable effort has been devoted to removing noise from medical images. The authors present a new method of image noise smoothing. This method uses the natural separation of distinct populations in each window to evaluate a given pixel. In this way, more pixels that belong to the population are included in the cluster of the given pixel, and fewer pixels that do not belong to the population are erroneously included. The image smoothing is further enhanced by the join-count statistic. By implementing join-count statistics, clusters that were erroneously separated by a large variation of random noise were evaluated and merged. This operation provides better results, enhancing noise smoothing, especially in the areas with largely uniform pixels. As a result, the smoothing performance is enhanced while the preservation of edges is maintained. >

Noise quenching method and apparatus for a colour display system

Abstract: An apparatus and method for suppressing noise and an input image having a plurality of pixels, each of the pixels in the plurality of pixels having a range of possible values between at least two extremities. A first group of pixels is determined, each pixel of the first group having a value that is less than a predetermined amount from the value of at least one of the extremities. The values of pixels adjacent to each pixel in the first group are examined to determine if the adjacent pixels are also members of the first group and, when a predetermined number of the pixels adjacent to a pixel in the first group are also members of the first group, reassigning the pixel value of that pixel in the first group and each of its adjacent pixels to have the value of at least one of the extremities.

Method and apparatus for processing image data.

Abstract: A first image data representing an image containing a plurality of first pixels at first density is converted into a second image data representing the image by a plurality of second pixels at a second density which is a selected multiple of the first density. For each of the first pixels which are overlapped with the second pixels, the ratio of the size of the overlapped portion to the size of the first pixels is determined on the basis of the selected multiple. The weighted mean of the pixel signals representing each of the first pixels overlapped is calculated by the weight coefficients determined by the corresponding ratio, thus obtaining the pixel signals representing the second pixels. Also, before the first image data are converted into the second image data, the first image data is subjected to a given correction process as required. This correction process is carried out as follows: the constants of correction of the given correction process for each of the pixel signals of the first pixel data are determined; the pixel signals are divided into a plurality of bit blocks so that each block contains a given number of bits; a given mathematical operation is executed on the number represented by each of the bit blocks of each pixel signal, and the constants for the correction determined for each pixel signal to determine corrected partial data; and corrected pixel signals are generated by combining the corrected partial data obtained for each of the plurality of bit blocks of each pixel signal.

New method of noise smoothing based on gray level and spatial separation

Abstract: Medical images produced by x rays as the energy source are subject to contamination by random noise due to the statistical nature of both the x rays and the electomagnetic field. This noise degrades the image quality. There has been a considerable amount of effort devoted to the removal of noise in medical images. The purpose of this project is to introduce a new method that utilizes the natural separation of different populations of pixels with the same gray-level characteristics to smooth image noise efficiently while effectively preserving edges. The assumption is made that pixels inside a small window can be separated into two populations. Only the pixels belonging to the correct population will be used for filtering. Thus smoothing performance is enhanced while maintining the preservation of edges since pixels from the other population are not included in the evaluation. The new filter involves two steps: (1) Pixels are clustered according to their gray-level characteristics. (2) The central pixel is replaced by a weighted averaged value from the population containing the central pixel. The weight is determined by the distance of a given pixel from the central pixel. Preliminary results show effective noise smoothing especially where there is a large uniformity of pixels. Furthermore, there is preservation of edges.