Showing papers on "Bilateral filter published in 2000"

Methods and apparatus for analyzing and image and for controlling a scanner

Abstract: A method analyzes an image to be scanned and analyzes at least part of the image pixel-by-pixel. During or after a preview scan, a characteristic is assigned to a plurality of pixels in the image and pixels are grouped according to similar characteristics. A representation of a least one of the characteristics corresponding to a group of pixels is communicated to the scanner. For example, the pixels may be analyzed to determining if the pixel is black or white. The pixels may also be analyzed to determining if a pixel is on an edge between black and white. Black pixels that are adjacent each other can be grouped together, and white pixels that are adjacent each other can also be grouped together. A region of an image with a relatively high number of black and white groups can be characterized as black and white text only. That characterization can then be used to properly set a scanner, for example, without user intervention, so that the final scan of the image can be done at 300 dpi with a low bit depth.

Method for determining storm predictability

Abstract: A method and apparatus for determining the predictability of an element in a weather radar image. An image filter approximating the envelope of the organized storm radar image is applied to a pixel in a received weather radar image to generate a processed pixel value. A variability value is determined from the variation in the pixel values of the neighboring pixels which lie within the image filter. The predictability is generated from the processed pixel value and the variability. Pixels having high processed pixel values and low variabilities typically correspond to pixels within a strong organized storm and, therefore, are more predictable. Pixels having low processed pixel values and high variabilities, such as pixels representative of airmass storms, generally have lower predictabilities.

Correcting defect pixels in a digital image

Abstract: Systems and methods of correcting one or more defect pixels in a source image are described. The source image is formed from a plurality of pixels each having a respective value. In one scheme, a defect pixel is corrected based upon curvature information computed from pixel values located near the defect pixel. In another scheme, a median pixel value is determined from values of pixels located near a defect pixel, and the defect pixel is corrected based upon the median pixel value.

Method for real time correlation of stereo images

Abstract: In a method for correlating two stereo images, the images are subjected to a Laplacian operator and further processed to produce reduced gray scale Laplacian images in which the pixels have a value of +1, 0 or −1. Then the two images are overlapped to produce pairs of overlapping pixels. The values of the two overlapping pixels are summed in a manner so that if both pixels are +1 or both pixels are −1 the summed value is +1, if one pixel is +1 and the other pixel is −1, the resulting sum is −1 and if one or both pixel are zero, the resulting sum is zero. All of the sums or correlation values in regions about each pixel in the two overlapping images are added together to get a new correlation value for each pixel in the overlap resulting in a correlation image. Then, the two Laplacian images are shifted relative to one another and correlation values are again computed for this new overlap. This process is repeated several times resulting in correlation values for each overlap. For each pixel, the overlap which has the highest correlation value is the best match. Having determined the best match one can then determine the location of an object or point in the field of view using standard stereo processing techniques.

Multiresolutional critical point filter and image matching using the invention

Abstract: A multiresolutional filter called a critical point filter is introduced. This filter extracts a maximum, a minimum, and two types of saddle points of pixel intensity for every 2×2 (horizontal×vertical) pixels so that an image of a lower level of resolution is newly generated for every type of a critical point. Using this multiresolutional filter, a source image and a destination image are hierarchized, and source hierarchical images and destination hierarchical images are matched using image characteristics recognized through a filtering operation.

Removing chroma noise from digital images by using variable shape pixel neighborhood regions

Abstract: A method for removing noise on a pixel by pixel basis from pixels of a digital image is disclosed. The pixels are used to produce a map of features, which then are used to produce a variable shape neighborhood region of cleaning pixels with respect to the original value of the pixel of interest. The neighborhood region of cleaning pixels and the value of the pixel of interest are then used to change the original value of the pixel of interest in the digital image so that it has been noise cleaned.

Image enhancement filter with adaptive threshold

Abstract: A method of adaptive spatial filtering for enhancing digital images is presented. A window is applied to a source pixel to generate an array of windowed pixels. An upper threshold value and lower threshold value corresponding to the maximum and minimum pixel values, respectively, in the array of windowed pixels are determined. A spatial frequency filter is applied to the array of windowed pixels to generate a filtered array of pixels including a reference pixel. The values of the source pixel and the reference pixel are scaled by respective weighting factors and then combined to create an enhanced pixel value. If the enhanced pixel value exceeds the upper threshold value, the enhanced pixel value is replaced by the upper threshold value. Similarly, if the enhanced pixel value is less than the lower threshold value, the enhanced pixel value is replaced by the lower threshold value. The resulting array of enhanced values provides greater edge transitions yet does not result in overshoot and undershoot regions which are generated by many traditional edge enhancement methods. In addition, color shifts associated with independent processing of individual color planes are avoided.

Method and apparatus for driving liquid crystal display panel in inversion

Abstract: A method and apparatus for driving a liquid crystal panel in a line-inversion system is disclosed. In the method, at least one pixel block each of which includes at least two data lines within the liquid crystal panel is set. The adjacent pixels in a gate line direction within the pixel block respond to data signals having the same polarity. The pixels within the other pixel areas except for the pixel block respond to data signals having a polarity contrary to the adjacent pixels at the left and right sides thereof. Accordingly, a current amount charged in the adjacent pixels having a large brightness difference is supplied always equally, so that the brightness difference between the adjacent pixels can be reduced to eliminate a noise pattern in the vertical direction.

Panel detector pixel replacement method and apparatus

Abstract: A technique for generating replacement values for defective pixels in a digital imaging system includes generating a base values for the defective pixels and a statistical characterizing values which provide consistent statistical relationships with other pixels The base values may be computed as mean values of pixels surrounding the defective pixels The statistical characterizing values may be selected to provide deviation from the mean values by a standard deviation of other selected pixels, such as pixels in the neighborhoods of the defective pixels The technique avoids image artifacts due to inconsistent noise or other statistical characteristics in the pixel replacement values

Filter and image device provided with filter

Abstract: PROBLEM TO BE SOLVED: To provide a filter which has a higher opening ratio than a filter using a mesh and in which a moire pattern is hardly visible when the filter is disposed in front of an image device having square pixels. SOLUTION: In a transparent filter on which many linear conductive materials are arranged on the surface of a sheet body to be disposed in front of an image device having square pixels, the conductive materials having =70%. The P1, P2 and the lengths W1 and W2 of the pixel in the image device along the vertical direction and the horizontal direction, respectively, satisfy the relation of n1 +0.35<=W1/P1<=n1+0.65 and n2+0.35<=W2/P2<=n2+0.65.

Filtering of defective picture elements in digital imagers

Abstract: Defective pixels in a CMOS array give rise to spot noise that diminishes the integrity of the resulting image. Because CMOS arrays and digital logic can be fabricated on the same integrated circuit using the same processing technology and relatively inexpensive and fast circuit can be employed to digitally filter the pixel data stream and to identify pixels having values that do not fall in the range defined by the immediately neighboring pixels and the deviate from the neighboring pixels by more than a threshold amount. Such conditions would indicate that the deviation is caused by a defective pixel rather than by desired image data. The threshold amount can be preprogrammed or can be provided by a user or can be dynamically set using feedback indicating image quality. The filter would also provide a solution for other sensors such as CCD.

Edge enhancement method by 4-directional 1-dimensional high pass filtering

Abstract: An edge enhancement method by 4-directional 1-dimensional high pass filtering characterized in that 4 adjacent pixels positioned at a pixel point at which the primary pixel has euclidean distance of 2 in direction of right, left, up, and down, another 4 adjacent pixels positioned at a pixel point at which the primary pixel has euclidean distance of 22 in 45° and 135° direction, and 9 pixels including the primary pixel are masked by a window mask, and if the maximum difference of the surround pixels which are masked is greater than a predetermined reference difference, each edge enhancement value is calculated by performing 1-dimensional high pass filtering in column, row, 45°, and 135° direction centered from the primary pixel using the pixel values which are masked to the window mask. If the primary pixel is greater than the average value of the pixels which are masked to the window mask, the primary pixel is substituted by the maximum edge enhancement value among the above-calculated each edge enhancement value. If the primary pixel is less than the average value of the pixels, the primary pixel is substituted by the minimum edge enhancement value.

Image compression and decompression based on a flat pixel group level, group pixel coorindinate positions, and the number of pixels for the group

Abstract: An encoding apparatus whereby image signals provided in units of frames, each having a plurality of pixels, are divided into macro groups, and the pixels in each macro group are combined, forming a group. The pixels of the group are encoded on the basis of the level data representing the signal level of the representative pixel in the group, the position data concerning all pixels of the group and the data representing the number of the pixels existing in the group.

Method of processing, and corresponding filtering device

Abstract: The invention relates to a method of processing data, which may be pixels (P[i,j]) representing a sequence of pictures, previously encoded and decoded. The method comprises at least in series a first step (ED) of detecting edge pixels within a picture, followed by a subsequent step (TEST) in which a choice is made from the pixels not detected as edges in the previous step, as to whether these pixels are to be filtered or not. Then, the method comprises a filtering step (SAF) which consists in replacing at least a pixel to be filtered with a pixel belonging to a close neighborhood of said pixel, said close neighborhood comprising said pixel and pixels adjacent to said pixel.

Method and an apparatus for elimination of color Moiré

Abstract: A digital image processing method for eliminating Moire in a digital image divided into pixels holding pixel component values includes selecting a first pixel and defining a pixel window around the selected first pixel. Then, a set of pixels are identified which consist of pixels within the window that have pixel component values within a pixel component value range that is related to the selected first pixel. A pixel component value is calculated based on corresponding pixel component values of pixels in the set of pixels and then this calculated pixel component value is allocated to the selected first pixel.

Fuzzy Weighted Average Filter

Abstract: This paper mainly studied the problem of the noise suppression for images corrupted by different kinds of noises. A weighted average filter based on the fuzzy theory is presented. The algorithm first looks on the pixels in the filter window as elements of a fuzzy set, and then optimizes the membership of each element of the fuzzy set by iteration ways. In the end, the filter gets its weights of the pixels in the window from the memberships of the fuzzy set. Computer simulations show that the presented filter is not only better than average filter in the field of suppression of Gaussian noise, but also good at the suppression of impulse noise. So it has good performance to image corrupted by mixture noise.

Enhancing an image, such as an image having bi-valued pixel values

Abstract: A method is proposed for converting an image in which each pixel takes one of two binary values, into an image in which each pixel can take continuous values. The method is iterative and works in the space domain. For each pixel, a neighborhood of the image is defined containing that pixel and other pixels. In a first iteration, the method obtains a continuous value for each pixel as a weighted sum of the binary values of the pixels in its neighborhood. In further iterations, the method obtains a continuous value for each pixel as a weighted sum of the values of the pixels in its neighborhood at the previous iteration.

Removal of mixed noise on color image processing by using fuzzy rules

Abstract: We have proposed fuzzy filters in order to remove additive non-impulsive noise (e.g., Gussian noise)while preserving signal details. In this paper, we propose a novel fuzzy filter for removing mixed noise(i.e., Gaussian noise and impulse noise are mixed). Furthermore, we apply the proposed method to colorimage processing. In order to remove mixed noise efficiently, we set fuzzy rules by using multiple dii-ference values between arbitrary two pixels in a filter window. We show tuning result of the proposedfuzzy filter and present some simulation results. 1. Introduction Since the first introducing of Fuzzy Set Theory [1] fuzzy techniques for image processing applicationshave mainly detail with high-level computer vision and pattern recognition [2]. Only recently, however,fuzzy techniques have successfully entered the area of low-level computer vision for general purposeapplications becoming competitive with classical methods in some very important pre-processmg tasks.In particular, focusing on the area ofnonlinear filtering of noisy image data, many original approacheshave been proposed in the last few years[3-lOJ.Taguchi and Takashima propose a fuzzy filter which is one ofnonlinear filter for noisy image data, in[8]. This fuzzy filter is an adaptive weighted average filter whose weight derived by using fuzzy rules.The antecedents offuzzy rules are constructed by using two important local characteristics: the differ-ence value from centre pixel's value and the distance from centre pixel. Since the fuzzy filter is able tochange its property according to local characteristics, it can remove non-impulse noise (e.g., Gaussiannoise) while preserving details. However, the fuzzy filter isn't able to remove impulse noise, becausethe difference value from centre pixel's value which one of local characteristics, is very sensitive toimpulse noise.In this paper, we propose a novel fuzzy filter which is able to remove not only non-impulse noise butalso impulse noise, since we introduce a new local characteristics to the fuzzy filter. A new local char-acteristic is calculated by using multiple difference values between arbitrary pixels in the filter window.The proposed filter can be applied to color image processing. Thus, we also propose the fuzzy filter forcolor image processing.In Section 2, we introduce a new local characteristic for filtering. Furthermore we also show thesame concept local characteristic for color image processing. In Section 3, we propose a novel fuzzyfilter for monochrome and color images, which is called a modified fuzzy (MF) filter, by using these

Image processing unit, image processing method and medium

Abstract: PROBLEM TO BE SOLVED: To conduct information imbedding, without causing quality of images to deteriorate or data quantity to increase. SOLUTION: An imbedding coder 3 selects a part of pixels of an image and imbeds additional information to the pixels by rotating the value of the selected pixels according to the additional information, and outputs the imbedded image. An imbedding decoder 6 selects a part of pixels of the imbedded image and rotates the value of the selected pixels by the prescribed number of bits. Furthermore, correlation between the pixels, whose value is rotated and the pixels other than the selected pixels, is calculated and number of bites for the rotation to decide the selected pixels is decided on the basis of the correlation. Then the selected pixels and the additional information imbedded to the pixels are decoded, on the basis of the decided number of bits.

Device and method for filtering

Abstract: The invention relates to a method of processing data, which may be pixels (P[i,j]) representing a sequence of pictures, previously encoded and decoded. The method comprises at least in series a first step (ED) of detecting edge pixels within a picture, followed by a subsequent step (TEST) in which a choice is made from the pixels not detected as edges in the previous step, as to whether these pixels are to be filtered or not. Then, the method comprises a filtering step (SAF) which consists in replacing at least a pixel to be filtered with a pixel belonging to a close neighborhood of said pixel, said close neighborhood comprising said pixel and pixels adjacent to said pixel.

Time space and control method, time spatial filter, and storage medium recording time space band limit program

Abstract: PROBLEM TO BE SOLVED: To provide a time spatial filter that increase an information amount whose band is limited even from a video image including multiple edge pixels at the outside of a target area. SOLUTION: An edge detection section 103 detects an edge of a received image and an edge information storage section 104 stores edge information. An edge density measurement section 105 measures the edge density of an edge pixel and an edge target area discrimination section 105 determines whether or not the edge pixel is in a target area. When the edge pixel is in the target area, a filter control section 107 sets a frequency characteristic of a filter F1 to a characteristic C1. When the edge pixel is in a non-target area, the filter control section 107 sets the frequency characteristic of the filter F1 to a characteristic C2. A filter selection section 108 selects the filter F1 when a pixel receiving filtering is an edge pixel. The filter selection section 108 selects a filter F2 when a pixel receiving filtering is not an edge pixel. COPYRIGHT: (C)2001,JPO

Digital still picture camera, has pixels arranged in solid imaging element so that every pixel in odd series is shifted only by half horizontal pixel spacing

Abstract: The camera has an optical system for generating an image of an object which is to be imaged by a color filter arrangement (7), and includes a solid imaging element which has a photo diode and load connected storage element, that in each case corresponds to a pixel from a uniformly arranged number of pixels. Picture signals are generated by photoelectric conversion through the optical system. The majority of pixels are arranged in the solid imaging element so that every pixel of an odd series is shifted only by half of the horizontal pixel gap spacing wit regard to neighboring pixel of a neighboring even series. The color filter arrangement is arranged so that the filters corresponding to every pixel are arranged for direction in the horizontal direction repeatedly in the sequence of red filters, green filters and blue filters. The filter corresponds to three pixels (8R,8G,8b), formed from two neighboring pixels in the horizontal direction and a pixel neighboring the two pixels in a vertical direction. The filter consists of a red filter, green filter and blue filter, the positions of which coincide with the positions of a red luminous material, green luminous material and blue luminous material of a color CRT shadow mask.

A probabilistic image model for smoothing and compression

Abstract: In this paper, the problem of edge preserving smoothing in image processing is tackled by combining a noise corruption model and a region and edge image model. The derivation of the probability model for the first order difference in the gray levels of the region pixels and edge pixels leads to a non-linear filter with coefficients as functions of the estimated noise variance and edge intensity. Such a model-based approach allows the design of improved filters for noise filtering and image compression. Experimental results demonstrate the improved performance of the filter for both synthetic and natural images.

Probabilistic nonlinear diffusion image filter

Abstract: A stochastic image model is proposed for edge preserving smoothing. The derivation of the probability model for the first-order difference in the gray levels of the region pixels and edge pixels lead to a nonlinear filter with coefficients as functions of the estimated noise variance and edge intensity. Such a model-based approach enables the design of improved filters for noise filtering. Experimental results demonstrate the improved performance of the filter for both synthetic and natural images.

A tunable fuzzy filter based on differences between pixels

Abstract: This paper presents a new fuzzy filter structure for edge-preserving smoothing of an image corrupted by impulsive and white Gaussian noise. This filter structure is expressed as an adaptive weighted mean filter that uses fuzzy control. The coefficients of the proposed filter can be varied adaptively by fuzzy control laws based on differences between pixels in the window. The parameter of this filter can be adjusted by learning. Finally, simulation results demonstrate the effectiveness of the proposed technique.