Showing papers on "Bilateral filter published in 2001"

Image-based modeling and photo editing

Abstract: We present an image-based modeling and editing system that takes a single photo as input. We represent a scene as a layered collection of depth images, where each pixel encodes both color and depth. Starting from an input image, we employ a suite of user-assisted techniques, based on a painting metaphor, to assign depths and extract layers. We introduce two specific editing operations. The first, a “clone brushing tool,” permits the distortion-free copying of parts of a picture, by using a parameterization optimization technique. The second, a “texture-illuminance decoupling filter,” discounts the effect of illumination on uniformly textured areas, by decoupling large- and small-scale features via bilateral filtering. Our system enables editing from different viewpoints, extracting and grouping of image-based objects, and modifying the shape, color, and illumination of these objects.

Filtering of multichannel SAR images

Abstract: An explicit form of the linear multichannel synthetic aperture radar (SAR) intensity filter, which preserves radiometry while optimally reducing speckle is derived, together with a compact expression for the theoretical gain in equivalent numbers of looks (ENLs). The filter can be applied to mixed data types, which is demonstrated using a combination of ERS and JERS satellite data, and confirms the filter performance predicted by the theory. Tests indicate that a simplified form of the filter, which neglects correlation between images, gives an ENL only slightly less than optimal, while being much easier to implement. Exact analysis of the effect of estimating filter weights shows that the linear increase in ENL with the number of images predicted for the ideal filter does not occur. In practice, the ENL is affected by the window size used to estimate the weights and saturates as the number of images increases. An efficient recursive form of the filter is described, which is most naturally applied to multitemporal data for the practically important case where the current image is uncorrelated with previous images in a data sequence.

Encoding and decoding a message within an image

Abstract: A method for decoding a message embedded in a pattern of pixels. The method includes the steps of determining the pixel values for pixels from the pattern of pixels, determining binary values from the pixel values for pixels from the pattern of pixels; and determining the embedded message from the binary values. The pixels have a range of pixel values between a maximum and a minimum. The pixels are divided into cells each having glyph cell and background pixels. The binary value of a glyph pixel is determined by the contrast the glyph pixel has with its background pixels. The method can be used to decode embedded web-site address from an image with a foreground image and the embedded web-site address.

Method and apparatus for motion adaptive deinterlacing

Abstract: An adaptive filter calculates a target pixel from an interlaced video signal. The video signal comprises a plurality of frames, each of which comprises an even and an odd field. The filter comprises a quantized motion calculator and a filter selector. The quantized motion calculator estimates an amount of motion about the target pixel. The filter selector selects a filter in accordance with the estimated amount of motion. The filter applies a first weighting factor to a plurality of current field pixels and a second weighting factor to a plurality of previous field pixels for creating the target pixel.

Image background replacement method

Abstract: An image's pixels are initially segmented into pixels of the image foreground and background by comparing the pixels of the image to updated models of background reference pixels. Pixel structures are identified in the image. The probability that a pixel is in the background or foreground is refined by considering the initial segmentation of the pixel's neighbors and the pixel's membership in a pixel structure. If a pixel is identified as a background pixel it is replaced by a pixel of a new background.

Method and apparatus for detection and removal of scanned image scratches and dust

Abstract: To avoid generating visible artifacts in the image, such as those generated when mildly defective areas are not identified, a system and method for identifying and correcting defects in a digital image including adjusting the pixel values of pixels surrounding the defective pixels are disclosed. The method for correcting defects in a input digital image comprises the steps of identifying the defects to form at least one defect map, generating a region of interest for each defect map, correcting the values of the pixels in each defect map, and adjusting the values of the pixels in each region of interest.

Bilateral Filtering and Anisotropic Diffusion: Towards a Unified Viewpoint

Abstract: Bilateral filtering has recently been proposed as a noniterative alternative to anisotropic diffusion. In both these approaches, images are smoothed while edges are preserved. Unlike anisotropic diffusion, bilateral filtering does not involve the solution of partial differential equations and can be implemented in a single iteration. Despite the difference in implementation, both methods are designed to prevent averaging across edges while smoothing an image. Their similarity suggests they can somehow be linked. Using a generalized representation for the intensity, we show that both can be related to adaptive smoothing. As a consequence, bilateral filtering can be applied to denoise and coherence-enhance degraded images with approaches similar to anisotropic diffusion.

Method for cross-fading intensities of multiple images of a scene for seamless reconstruction

Abstract: A computer implemented method cross-fades intensities of a plurality of overlapping images by identifying pixels in a target image that are only produced by a first source image. The weights of all the corresponding pixels in the first source image are set to one. Pixels in a second source images contributing to the target image are similarly identified and set to one. the weight of each remaining pixel in the first and second images is inversely proportional to a distance to a nearest pixel having a weight of one. Then, the first and second source image can be projected to form the target image.

A New Filtering Algorithm Based on Extremum and Median Value

Abstract: A new median based filtering algorithm-extremum median filtering is presented In order not to perturb the efficient signals as much as possible when the noises are removed, the following approaches are developed in this paper First, all the pixels are separated into signal pixels and noise pixels according to the decision criterion given in the following; then, noise pixels are replaced with the median value of their neighborhood in the input image The decision criterion: if a pixel value is the extremum (max or min) of its neighborhood, it is a noise pixel; else, it is a signal pixel This decision criterion is under such an assumption: inherent relationships exist among neighbor pixels If a pixel value is far higher or lower than the others' value of its neighborhood are, that is to say, a pixel has lower correlation with its neighbors, we may consider that it had been contaminated with noise Else, if it is similar to the others, we consider that it represents an effective signal Experimental results show that the assumption fits the facts quit wellIn this paper, attention is forcused on filtering of images degraded by "salt and pepper" noises Examples on images containing 184×148 pixels are givenExperimental results show that the EM filtering has better performance than standard median filtering with less subtle details being eliminated The SNR of the image filtered with EM filter is about 4dB higher than that with median filter This is because the operation only affects noise pixels and most of the uncontaminated pixels keep intact Especially,in the case of lower SNR,larger filtering window improves the SNR notably Median filter is not the case, for the filtering operation blurs the image extremely with the increasing of the filtering window

Motion detection via image alignment

Abstract: Pixels of an image are classified as being stationary or moving, based on the gradient of the image in the vicinity of each pixel The values of corresponding pixels in two sequential images are compared If the difference between the values is less than the image gradient about the pixel location, or less than a given threshold value above the image gradient, the pixel is classified as being stationary By classifying each pixel based on the image gradient in the vicinity of the pixel, the sensitivity of the motion detection classification is reduced at the edges of objects, and other regions of contrast in an image, thereby minimizing the occurrences of ghost artifacts caused by the misclassification of stationary pixels as moving pixels

Moire correction in images

Abstract: Image defects in a digital image are reduced by a process comprising providing a digital image data set in the form of a matrix of pixels; selecting a sub-matrix comprising at least a 5×5 matrix of pixels; identifying a pixel within the sub-matrix to be treated as a central pixel; determining a value for at least one optical property in the central pixel; selecting at least four pixels around the central pixel as averaging pixels, at least two of the averaging pixels being in a position in the sub-matrix that is not adjacent the position in the matrix of the central pixel; determining a value for the at least one optical property for the at least four averaging pixels; averaging the values for the at least one optical property for more than one of the at least four averaging pixels to provide an average treatment value for the central pixel; assigning the average treatment value for the central pixel to the central pixel; and storing the average treatment value assigned to the central pixel.

Imaging-based distance measurement and three-dimensional profiling system

Abstract: A method and apparatus for determining the distance of each pixel or a set of pixels in images acquired by cameras and thus imaging the three-dimensional profiles of objects in the images is described A source of illumination is projected through a mask of two-dimensional pattern onto the objects and images from predetermined and different view points are captured by a camera or cameras. A computer algorithm is used to identify a pixel or a set of pixels in each area of the pattern in each acquired image. The distance of the pixel or the set of pixels in the images is uniquely calculated by using the X, Y coordinates of the pixel or the set of pixels in the images of different view points and the positional relationship of the different view points. The three-dimensional profile of objects in the images is determined by collecting the distance information of each pixel or an area of pixels in the images.

Generating resized images using ripple free image filtering

Abstract: An optimal filter kernel, formed by convolving a box filter with a filter of fixed integer width and unity area, is used to perform image resizing and reconstruction. The optimal filter has forced zeros at locations along a frequency scale corresponding to the reciprocal of the spacing of one or more pixels that comprise a source image to be resized. When a rescale value for a source image is selected, the optimal filter kernel is computed, mapped to the source image, and centered upon a location within the source image corresponding to the position of an output pixel to be generated. The number of pixels that lie underneath the optimal filter kernel is established by multiplying the number of pixels that comprise the width of the source image by the selected rescale value. Upon mapping the optimal filter kernel, the output pixel values that comprise the resized image are then evaluated by processing the one or more source image pixels, such as through interpolation. Alternatively, the output pixel values of the resized image are calculated by performing partial integral analysis with respect to a standard filter kernel of fixed width and unity area. The output pixel values are calculated by multiplying the pixel value for each pixel under the kernel by the area of the standard filter kernel surrounding the pixel. The products are then summed to reveal the output pixel value, and placed into the output image buffer. Both of these methods speed up the computation process, while producing a ripple free output image.

Out-of-layer pixel generation for a decomposed-image layer

Abstract: Images may be decomposed into separate layers each containing a limited number of types of image element (text, line art, or photographic). Each layer can then be compressed separately with a process that is optimal for the type of image element included in the layer. Images are decomposed into foreground, background, and mask layers. A method is provided for generating the out-of-layer pixels and, as a result, generating a layer having a limited color palette that is to be compressed with a palette based lossless compression method. A plurality of neighboring pixels is identified for each pixel selected from the image. If the neighboring pixels are out-of-layer pixels, the spatially corresponding pixel in the decomposition layer is assigned a default value. If the neighboring pixels include in-layer pixels, the pixel of the decomposition layer spatially corresponding to the selected pixel is assigned the predominant color of the in-layer neighbors. If equal numbers of the neighboring pixels have the same colors then the selected pixel is assigned the value of a predetermined neighbor. If no two neighboring pixels have the same color then the spatially corresponding pixel is assigned the color that is most likely to occur in conjunction with pixels having the colors of the neighboring pixels.

Adaptive image filtering based on a distance transform

Abstract: A method for reducing visual artifacts in reconstructed images. One embodiment of the method determines edge energy for each pixel in the image and then compares the edge energy for each pixel to a threshold, producing an edge map. A distance transform is then used to produce a filter map and a filter is applied to pixel in the image, such that the filter applied is dependent upon a filter map value for each pixel. An output value for each pixel is then produced.

Image processing apparatus and storage medium for storing image processing program

Abstract: Smoothing that uses pieces of color information of at least one color component of a target pixel and of pixels adjacent to the target pixel among a plurality of pixels that form image data is performed selectively for at least one color component of the target pixel. The smoothing is in accordance with correlation between the target pixel and pixels in the vicinity of the target pixel. Since the entire image data is not smoothed uniformly, the smoothing can be performed so as to leave structures inherent to the original image.

Motion adaptive noise reduction method and system

Abstract: A method and system of noise filtering is provided. The pixels of a first filter mask are separated into groups based on luminance. . . . The sizes of each group is determined and a largest group is selected. The distance of each group of pixels from the largest group is also calculated. Pixels in groups that are small compared to the largest group and far from the largest group are tagged as noisy. After tagging the noisy pixels, additional filtering can be applied to the pixels of first filter mask without degradation from the tagged pixels.

Method of and apparatus for distinguishing type of pixel

Abstract: Halftone pixels are distinguished from non-halftone pixels in pixels making up an image according to a predetermined algorithm based on a result of edge detection for determining whether the pixels are edge pixels. The pixels which have been determined to be non-halftone pixels according to the predetermined algorithm, are continuous to the pixels determined to be halftone pixels according to the predetermined algorithm including those which have been redetermined to be halftone pixels and are not lower than a predetermined threshold density in density are all redetermined to be halftone pixels.

Method for depth detection in 3D imaging providing a depth measurement for each unitary group of pixels

Abstract: A method and apparatus for obtaining up to one depth measurement for each pixel. A image sensing array (ISA) captures a measurement of intensity on a surface. The intensity maps to depth. Accordingly, from a single pixel, or a group of pixels without regard to the intensity distribution among the pixels in the group, a depth measurement can be obtained independently of any and/or all data captured by other pixels in the array.

A method and apparatus for spatial light modulation

Abstract: The present invention includes a method to use a phase modulating micromirror array to create an intensity only image that has high image fidelity, good stability through focus and good x-y symmetry. The method uses pixels consisting of at least one tilting mirror element and adjacent pixels tilt in different ways, but they are laid-out in a pattern that creates effective averaging between pixels with different tilt. The pattern is such that even if a single pixel creates a reflecting or scattering pattern that is asymmetric relative to the specular direction every neighborhood consists of pixels that together create symmetry. The invention allows the use of single-mirror pixels instead of multi-element pixels, thereby making manufacturing and design easier and also makes a smaller pixel size possible. Particular aspects of the present invention are described in the claims, specification and drawings.

Correcting defective pixels in an image

Abstract: A source image formed from a plurality of pixels each having a respective value may have defective pixels (X). A defective pixel (X) is corrected based on curvature information computed from pixel values of pixels located near the defective pixel (X). Curvature is defined as being calculated by performing arithmetic functions on values of pixels in rows above and below a row containing the defective pixel (X) or on values of pixels in columns preceding and succeeding the column containing the defective pixel (X). A second independent claim is included which claims the correction of defective pixel values by determining a median pixel value from pixels on the same colour plane located near the defective pixel (X).

Image artifact removal technique for LCP

Abstract: A technique is provided that identifies screen and non-screen regions of a projected or displayed image to smooth and selectively remove moire from the screen regions while maintaining sharpness in the non-screen regions. Each pixel in the image is classified as a screen or non-screen pixel and then pixels in a predetermined surrounding area of each pixel are examined to check the classification of that pixel. A low pass filter is applied to pixels in the image, such that, when the low pass filter is applied, a center of the low pass filter is selectively shifted relative to a current pixel based on the examination.

Method and system for enhancing the performance of a fixed focal length imaging device

Abstract: A group of pixels obtained using an imaging device is converted into a group of pixels having an equal or lower count by receiving at least first and second input pixels having an initial intensity value, forming at least one intermediate intensity value from each of the first and second input pixels, and combining the intermediate intensity values formed from the first and second input pixels to form at least one output pixel. This allows the pixels formed to have improved signal-to-noise characteristics, and it reduces transmission rates. A feature of the present invention allows a distance between the imaging device and an object to be used to select the number of output pixels formed. Another feature of the present invention allows a change in distance between the imaging device and an object to be used to dynamically adjust the number of output pixels formed. A further feature of the invention allows a variable resolution image to be converted to a fixed resolution image.

Memory efficient image artifact removal technique for LCP

Abstract: A technique is provided that identifies screen and non-screen regions of a projected or displayed image to smooth and selectively remove moire from the screen regions while maintaining sharpness in the non-screen regions. Each pixel in the image is classified as a screen or non-screen pixel and then pixels in a predetermined surrounding area of each pixel are examined to check the classification of that pixel. A low pass filter is applied to pixels in the image, such that, when the low pass filter is applied, one or more pixels covered by the low pass filter are respectively replaced by one or more other pixels covered by the low pass filter based on the examination.

An approximation-weighted detail contrast enhancement filter for lesion detection on mammograms

Abstract: Presents a novel approximation-weighted detail contrast enhancement (AWDCE) filter for detecting lesions in digitized mammograms employing the Daub20 wavelet transform. The AWDCE filter is implemented by weighting each pixel in the detailed images of chosen levels by the factor that is transformed from corresponding pixels in the approximation image. This ADWCE filter implementation was evaluated with the more traditional methods by using the same publicly accessible database. Experimental results show that the AWDCE filter can automatically enhance the mass contrast while preserving the image details in different scales, and that its performance is better than in previous works, especially in the contrast improvement ratio.

An adaptive filter for removal of noise in interferometrically derived digital elevation models

Abstract: A low-pass filter that chooses the window size depending on the degree of smoothing required by detecting isolated as well as clustered noise in the DEM is developed and tested. In the noise-free case, the standard deviation of the values of the pixels inside a window increases as the size of the window increases, due to the inclusion of height values that are either lower or higher than the central pixel value. If the standard deviation of the window pixels decreases as the size of the filter window increases then the presence of noise, either isolated or clustered, is indicated. Changes in the value of the standard deviation of the window pixels as the window size is increased can thus be used to fix an appropriate window size. Given a specific window size, the 'sigma operator' (Lee, 1983) is used to produce a 'noise-free' estimate of the central pixel value. In this operation, the values of pixels within the window that lie between an upper and a lower limit are averaged. The median is preferred as the measure of central tendency in determining the lower and the upper limit, because the value of the median is less affected by the presence of a minority of aberrant pixel values, whereas the mean value is computed from the values of all pixels in the window, including noise pixels. Hence the smoothing operation employed in this study is called the 'modified sigma operator'. The performance of the modified sigma operator is compared with that of a median filter in removing noise present in InSAR DEM. The performance of the filter was evaluated by comparing the distribution of root mean square (RMS) error against percentage of pixels (Balan and Mather, 2000), for unfiltered and filtered DEMs. The results show that the adaptive lowpass filter is more effective in reducing noise in the DEM.

Bilateral filtering in the wavelet domain

Abstract: In this paper, we introduced several noise removing techniques in the wavelet domain, analyzed the properties of bilateral filtering. Following them, bilateral filtering in the wavelet domain was proposed. With this method, the properties of time-frequency localization and multiresolution of wavelets were used. At last, we demonstrated the efficient noise removing and sharpening of object boundaries and detailed structures by applying this image processing technique to different images.

Reconstruction of erroneus image values in a image composed of picture elements

Abstract: The method uses pixels located in an area around the pixel to be reconstructed. The method involves determining a local orientation of the pattern for the location of the pixel to be reconstructed based on the pixel values or pattern orientation of pixels located in the region of the pixel to be reconstructed. Pixels around the pixel are selected along a path which runs through the pixel to be reconstructed and is in the predetermined orientation. An average value is determined from the selected pixels and this average value is set as the value of the pixel to be reconstructed.

Nonlinear smoothing filter using adaptive radial clustering

Abstract: A novel adaptive nonlinear filter is proposed aimed at smoothing homogenous regions while maintaining image structures. The filter can be utilized as a pre-processing tool in image segmentation and edge estimation for improving the results. Several special features are introduced to the filter, including using local adaptive radial clustering and pixel filtering to exclude the influence of outliers and to maintain image structures; using the steepest-ascent method to iteratively update pixels to the nearest clusters obtained by mean-shift; and introducing highly parallel processing by using random seed samples and their associated data blocks which enables fast processing and the global optimum solution of the nonlinear filter. Experiments were done on images of various complexities, and good results were obtained. Evaluations of the filter were also done in terms of edge preservation and image segmentation.

A method and an apparatus for elimination of colour moiré

Abstract: The present invention relates to an image processing method and system for reduction of Colour Moire that are simple and efficient. In particular, the present invention relates to a digital image processing method of eliminating Moire in a digital image divided into pixels holding pixel component values selecting a pixel, defining a pixel window around the selected first pixel, identifying a set of pixels consisting of pixels within the window that have pixel component values within a pixel component value range that is related to the selected first pixel, calculating a pixel component value based on corresponding pixel component values of pixels in the set of pixels, and allocating the calculated pixel component value to the selected first pixel.