39 results about "Edge-preserving smoothing" patented technology

A method for treating noise in low-dose computed tomography projections and reconstructed images comprises acquiring raw data at a low mA value, applying a domain specific filter in a sinogram domain of the raw data, and applying an edge preserving smoothing filter in an image domain of the raw data after filtering in the sinogram domain.

A system and method of image processing for smoothing, denoising, despeckling and sharpening scanned document images which is performed prior to a compression. The scanned image is selectively smoothed by anisotropic diffusion filtering in a single iteration with a 3×3 kernel, which provides denoising, edge-preserving smoothing. The smoothed image data is then selectively sharpened using variable contrast mapping that provides overshoot-free variable-sharpening and despeckling. Image quality is improved while increasing compressibility of the image.

The image processing apparatus and method process image data of an original image by compressing a dynamic range of the original image. The apparatus and method process the image data of the original image by continuous filtering with at least two edge preserving smoothing filters having different characteristics to generate blurred image data which represents a blurred image of the original image, and process the image data of the original image by compressing the dynamic range of the original image based on the blurred image data. The apparatus includes a blurred image generating unit for generating the blurred image data and having the at least two edge preserving smoothing filters, and a processing unit for compressing the dynamic range of the original image.

The present invention relates to the technical field of seismic data processing, and in particular to a seismic data edge preserving smoothing method based on structural features, which performs targeted sub-region de-noising treatment based on the structural information of seismic data and the similarity information of the pre-filtering process. In addition to the random noise removal, the method effectively protects the boundary information of seismic data. The edge preserving smoothing method includes steps of smoothing the seismic data, decomposing the matrix to obtain the structure tensor of the seismic data, and completing the structural feature analysis of the seismic data; using the conventional de-noising method to filter the seismic data and obtaining the local similarity coefficient; building a guide filtering equation; and performing multiple de-noising iterations and other steps.

A method of smoothing data to reduce or remove noise while preserving edge information in the data selects an output point in the data, identifies the most homogeneous neighborhood around the selected output point and outputs a corrected value for the selected output point based upon data points in the identified neighborhood.

The invention discloses a method for correcting the infrared focal plane heterogeneity based on a sigma filter. According to the method, sigma filter with the template size of 5*5 is performed on an image after linearity correction, self-adaptive adjustment of the iteration step length of a correction parameter and detection and replacement of abnormal pixels (bad pixels, impulse noise and the like) are completed when edge-preserving smooth filter is achieved, motion detection is achieved by using a change reference image, and only when the difference between the corrected image and the change reference image is larger than a change threshold value, update of the self-adaptive iteration step length is performed on the heterogeneity correction parameter. The sigma filter is applied to correction of the infrared focal plane heterogeneity, the heterogeneity parameter estimation error is reduced by using the edge preserving characteristic, the 'ghost objects' inhibiting capacity is strengthened, simultaneously, the self-adaptive iteration step length and detection and replacement of the abnormal pixels are achieved through the sigma filter, the computational complexity is low, and the method is suitable for hardware circuits.

The present invention provides an image processing method for immediately producing panoramic images. In this method, two fish-eye cameras are used for capturing video information, and then, a streaming video is transmitted to an electronic device by wired or wireless technology after the video information is treated with a video encoding process and a streaming process. Therefore, an image processing application program installed in the electronic device is able to subsequently treat the streaming video with a video encoding process, a panoramic coordinates converting process, an image stitching process, and an edge-preserving smoothing process in turns, so as to eventually show a sphere panorama on the display of the electronic device. Moreover, by the utilization of a digital signal processor, the image processing application program is able to further process the sphere panorama to a plain panorama, a fisheye panorama, or a human-eye panorama.

The invention discloses an electrical imaging logging image stratum attitude identification method. With the actually measured micro-resistivity imaging logging data acting as the basis, the generated imaging logging dynamic images are preprocessed, edge preserving smooth filtering is performed on the preprocessed images, and then pole plate image local direction estimation, sine curve fitting based on the tangent value and bedding interface detection fine processing and optimization processing based on the optimization technology are performed so that an electrical imaging stratum attitude pick-up processing result map is obtained, and the stratum attitude is identified according to the electrical imaging stratum attitude pick-up processing result map. A full-well-section stratum attitude automatic pick-up method is provided by applying the image processing related technology so that errors caused by artificial pick-up work can be avoided, and interpretation efficiency can also be enhanced.

The invention relates to an automatic detecting method for appearance defects of a storage battery polar plate. The traditional way mainly adopts a visual inspection way to detect the appearance defects of the storage battery polar plate, thereby having high boundedness. The method comprises the following steps of: firstly acquiring a grayscale image of one side of the storage battery polar plate through a linear array charge coupled device (CCD) camera, and carrying out the edge-reserved smooth filtering treatment on the grayscale image; carrying out self-adaptive threshold value segmentation for the filtered image; and finally confirming an independent noise point, counting the number of all continuous candidate defect points, and outputting a defect alarming signal when the number is greater than a set threshold value. By adopting the edge-reserved smooth method, combining with the self-adaptive threshold value segmentation technology and adequately considering the area characteristics of the defect, the appearance of the storage battery polar plate can be accurately detected in real time. The automatic detecting method can efficiently and accurately detect the appearance defect of the storage battery polar plate. The method is high in speed, high in defect detection success rate and pollution-free.

An image processing device includes a first production part configured to apply a first smoothing process to an original image data by using a first edge-preserving smoothing filter to produce first image data that include a low-frequency image and an edge image, a second production part configured to apply a second smoothing process to a differential image between the original image data and the first image data to produce second image data that include a high-frequency image, and a synthesis part configured to synthesize the first image data and the second image data.

An image processing device for performing edge-preserving smoothing includes a reducing unit for reducing an input image; a reduced image smoothing unit for performing a smoothing processing on a reduced image generated by the reducing unit with edges preserved; and an edge-preserving enlarging unit for enlarging an image generated by the reduced image smoothing unit with the edges preserved. The edge-preserving enlarging unit performs a filtering processing by determining a pixel value of a target pixel for the filtering processing based on weighted addition of pixel values of respective reference pixels. Weighting coefficients for the pixel values of the respective reference pixels is set based on differences between a pixel value of the input image corresponding to the target pixel and pixel values of the respective reference pixels and based on distances between the target pixel and the respective reference pixels.

Provided are an image processing device, image processing method, and computer program which can accurately detect noise in an input image and eliminate or reduce the noise. A display device extracts a specific area including a target pixel from an input image and determines whether the boundary of noise is included in the specific area. If so determined, the display device performs filtering using a smoothing filter to smooth the target pixel. If not so determined, the display device performs filtering using an edge-preserving smoothing filter to smooth the target pixel. At this time, the display device determines whether to apply the result of the smoothing process using the edge-preserving smoothing filter, on the basis of the pixel values in the specific area, the result of the smoothing process using the edge-preserving smoothing filter, and the like.

The invention discloses a color image contrast enhancement method comprising the following steps that a color image is read, and the coordinates of each pixel and the color component values thereof are acquired; the mean value of all the color component values is calculated so that mean image data are generated; edge-preserving smoothing filtering processing is performed on the mean image data; small scale mean filtering processing is performed; a pixel contrast enhancement coefficient is calculated according to contrast enhancement control parameters; all the color component values are enhanced according to the pixel contrast enhancement coefficient so that enhanced color component values are obtained; and clamping processing is performed on the enhanced color component values and then the enhanced color component values are outputted. Besides, the invention also discloses an enhancement system performing the method. The enhancement system comprises a reading module, a mean calculation module, a smoothing filtering processing module, a mean filtering processing module, an enhancement coefficient calculation module, an enhancement module and an output module. Processing in an RGB space can be performed directly, and only one time of key smoothing filtering processing is performed so that calculation is simplified and the effect of contrast enhancement is great.

The invention relates to an improved seismic horizon velocity field calculation method applicable to prediction of formation pressure and belongs to the field of exploration of physical geography. According to the method, a subsurface formation is divided into a background formation section and a target formation section, wherein the velocity of the seismic horizon of the background formation section is obtained with a three-dimensional constraint DIX formula inversion method, and the velocity of the seismic horizon of the target formation section is obtained with a post-stack wave impedance inversion method; then, the velocity of the seismic horizon of the target formation section is subjected to three-dimensional edge-preserved smoothing processing, and the defect of high heterogeneity of the velocity of the seismic horizon of the target formation section is overcome; velocities of the seismic horizon of the background formation section and the seismic horizon of the target formation section are subjected to data fusion processing with a Gaussian weighted filtering method, and non-authentic mutation of the velocity of the seismic horizon at a transition region of the background formation section and the target formation section is effectively suppressed; accordingly, a seismic horizon velocity field for formation pressure prediction is obtained. The obtained seismic horizon velocity field has the characteristics of a local or regional stable field and has the consistent characteristics with the pressure field of the subsurface formation.

A method of tonally stabilizing a video sequence is provided herein. The method includes the following stages: automatically selecting one or more anchor frames from a sequence of frames; obtaining an anchor adjustment map for each selected anchor frame; applying an edge-preserving smoothing algorithm to the sequence of frames; generating for any given pair of smoothed frames, a robust set of pixels indicating pixels affected by external tonal fluctuation only; initializing an adjustment map for any given frame by applying the anchor adjustment map to accumulated color differences between pixels of the robust set of the given frame and the anchor frame; and completing the initialized adjustment map by predicting values of pixels in each adjustment map not included in the robust set by applying an interpolation at a color space for these pixels, wherein the adjustment maps are usable for tonally aligning the video sequence with the anchor frame.

An image processing device includes a first generating unit configured to generate smoothed image data including an edge portion by performing a smoothing process on original image data using an edge preserving smoothing filter; a second generating unit configured to generate first differential image data of a differential image between an image of the original image data and an image of the smoothed image data; a histogram generating unit configured to generate a differential histogram, which is a histogram of frequencies of difference values included in the first differential image data; a third generating unit configured to generate second differential image data by correcting the first differential image data using a correction amount, the correction amount for the first differential image data being calculated based on the differential histogram; and a synthesizing unit configured to synthesize the smoothed image data and the second differential image data.

The invention provides a method and a device for constructing a tripartite graph, and an electronic device. The method comprises the steps of obtaining a color image containing a target object and a bipartite graph of the color image; performing edge-preserving smooth filtering processing on the bipartite graph based on the color image to obtain a smooth filtering image of the bipartite graph; andconstructing a tripartite graph of the color image based on the smooth filtering image of the bipartite graph. In the embodiment of the invention, the pixel value of the edge region of the bipartitegraph is changed due to the bilateral characteristics of the edge-preserving smooth filtering. The pixel value of the pixel point of which the color and the spatial distance are similar to those of the foreground region tends to the foreground region. The pixel value of the pixel point similar to the background area tends to the background area. The pixel points which are not similar to the foreground area and the background area are still used as unknown areas. The process can reduce a plurality of pixel points with wrong marks. In this way, the area of the unknown areas is greatly reduced inthe obtained tripartite graph, manual participation is not needed in the process, and consumed time is short.

Local histogram-based filters may create non-photorealistic computer graphics effects. An edge-preserving smoothing filter processes a source image to generate a smoothed image. An orientation filter processes the source image to generate a smoothed orientation image. At least one of the orientation filter and the edge-preserving smoothing filter include a local histogram-based filter. The non-photorealistic effect filter may generate a fine detail image from the smoothed image and the source image. The fine detail image may be diffused according to the smoothed orientation image to generate a brush stroke image. The brush stroke image is combined with a base image to create a non-photorealistic image. Local histogram-based filters include a closest mode, a local median, and a dominant mode filter. Local histogram-based filters are determined by convolving a neighborhood filter with one or more offset-kernel images, each based on the application of a shifted tonal filter kernel to the source image.

The invention relates to a high-resolution optical imaging method based on nanoparticle calibration. The high-resolution optical imaging method comprises the following steps: (1) capturing images of asample and an optical imaging system point spread function PSF by using a common wide-field optical microscope; (2) obtaining initial estimation about the image through standard Tikhonov regularization deconvolution; (3) carrying out edge-preserving smoothing filtering on the initial estimation of the image; (4) calculating an adaptive priori regularization item of the image; and (5) obtaining the estimation of the clear image based on the deconvolution adaptive to the sparse prior. According to the method, an ordinary wide-field optical microscope can be used for achieving non-invasion damage, the diffraction limit can be broken through, the high spatial resolution is achieved, the method is simple, the detection time is short, the cost is low, and the quality of the obtained image is high.

A signal processing method is provided. The method includes: generating an output signal containing a high-precision component at a level not determined by quantization of an input digital signal by subjecting each of pixels constituting the input digital signal to a predetermined filter operation such that a set of predetermined number of pixels including a target pixel and surrounding pixels thereof is obtained, the operation is carried out on the surrounding pixels when a variation from the target pixel is within a predetermined threshold range, and the operation is carried out on the target pixel when a variation from the target pixel is out of the predetermined threshold range; separating the high precision component from the signal output from the edge-preserving smoothing filter; and adding the high precision component separated from the high-precision component separating part to the input digital signal.

The invention discloses a color image enhancement method based on L0 gradient minimization, which belongs to the color image processing field, and solves the problems that according to an existing enhancement method, the illumination of an image is not natural, when the scale selection is not appropriate, the edge-preserving smoothing of the illumination image is insufficient, a halo phenomenon occurs or the texture information and the structure information in the image cannot be well distinguished, so that the estimated illumination image is inaccurate, and the detail loss of the finally enhanced image is caused. The method comprises the following steps of converting a color image from an RGB space to an HSV space, and extracting an intensity component V as a grayscale image; constructing an optimal function of the L0 norm constraint sparse item, and inputting the gray level image into the optimal function; solving an optimal solution of an optimal function by using a semi-quadratic term separation method, and taking the optimal solution as an estimated illumination image; obtaining a reflection image based on the grayscale image and the illumination image; and carrying out reconstruction by using the illumination image and the reflection image, and converting the reconstructed illumination image and reflection image back to the RGB space to obtain a final enhancement result. The method is used for color image enhancement.

The invention belongs to the technical field of computer digital image processing, and particularly relates to a wide line detection algorithm based on a water flow method. The steps are that a landform altitude graph is constructed: an inputted color image is converted into a gray scale image, edge preserving smoothing is performed on the gray scale image by adopting guide filtering, and the landform altitude graph is constructed with image gray scale information acting as altitude data; a wide line response diagram is acquired through the water flow method: a roughness image of the smoothed image is calculated, pixel points with high roughness are selected to act as candidate water molecules through Otsu, the wide line response diagram is acquired through the water flow method on the landform altitude graph, and water flow method slope threshold and geometric threshold parameters are self-adaptively selected; and wide line extraction is performed: darkness information or lightness information of the inputted image is calculated so as to eliminate wrong line response, and smoothing is performed through certain morphological operation so that a final wide line detection result is acquired. According to the method, the line thickness can be detected, and the wide lines of different grain shapes and thickness can be self-adaptively detected so that the accuracy of wide line detection can be greatly enhanced.