Showing papers on "Top-hat transform published in 2006"

Image denoising with block-matching and 3D filtering

Abstract: We present a novel approach to still image denoising based on effective filtering in 3D transform domain by combining sliding-window transform processing with block-matching. We process blocks within the image in a sliding manner and utilize the block-matching concept by searching for blocks which are similar to the currently processed one. The matched blocks are stacked together to form a 3D array and due to the similarity between them, the data in the array exhibit high level of correlation. We exploit this correlation by applying a 3D decorrelating unitary transform and effectively attenuate the noise by shrinkage of the transform coefficients. The subsequent inverse 3D transform yields estimates of all matched blocks. After repeating this procedure for all image blocks in sliding manner, the final estimate is computed as weighed average of all overlapping blockestimates. A fast and efficient algorithm implementing the proposed approach is developed. The experimental results show that the proposed method delivers state-of-art denoising performance, both in terms of objective criteria and visual quality.

Quality-aware images

Abstract: We propose the concept of quality-aware image , in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted image. To demonstrate the idea, we build a practical quality-aware image encoding, decoding and quality analysis system, which employs: 1) a novel reduced-reference image quality assessment algorithm based on a statistical model of natural images and 2) a previously developed quantization watermarking-based data hiding technique in the wavelet transform domain.

Image synthesization method

Abstract: An image synthesization method, whereby a plurality of images, each of which has a partially overlapping image area, are synthesized to create a single synthetic image, comprises a determination step of inputting a plurality of image data sets that correspond to the plurality of images that are input, and of determining whether or not an image in the partially overlapping image area of each of images that are indicated by the plurality of image data sets includes mainly characters an image processing step of performing, for the plurality of image data sets that are input, image processing in consonance with a result of a determination performed at the determination step and an image synthesization step of synthesizing images that are indicated by the resultant plurality of image data, for which the image processing has been performed at the image processing step. With this arrangement, a plurality of images can be easily and effectively synthesized.

Image capturing apparatus and image capturing method

Abstract: An image-capturing apparatus includes an image-capturing unit configured to capture image data of a subject and to store the captured image data in an image-capturing operation; a speed detector configured to detect speed information; and a controller configured to control the image-capturing unit so that, in an automatic image-capturing process that is not based on a shutter operation of a user, a distance moved by the image-capturing apparatus is computed on the basis of information from the speed detector, and the image-capturing operation is performed in response to the fact that a computation result indicating that the image-capturing apparatus has moved a predetermined distance is obtained.

Contrast enhancement of images

Abstract: A method and system for contrast enhancement of an input image that utilizes luminance values of pixels of the input image to derive transforms. The method down-samples and partitions an image into sub-images whereby transforms are generated for selected sub-images. The selected sub-image transforms are used to generate an output transform which is applied to the input image for local contrast enhancement of the image. Furthermore, a decision method as to whether or not the input image is to receive local contrast enhancement wherein darkness features of the input image are compared to threshold values and combined into an expression which results in the determination.

General Adaptive Neighborhood Image Processing

Abstract: The so-called General Adaptive Neighborhood Image Processing (GANIP) approach is presented in a two parts paper dealing respectively with its theoretical and practical aspects. The Adaptive Neighborhood (AN) paradigm allows the building of new image processing transformations using context-dependent analysis. Such operators are no longer spatially invariant, but vary over the whole image with ANs as adaptive operational windows, taking intrinsically into account the local image features. This AN concept is here largely extended, using well-defined mathematical concepts, to that General Adaptive Neighborhood (GAN) in two main ways. Firstly, an analyzing criterion is added within the definition of the ANs in order to consider the radiometric, morphological or geometrical characteristics of the image, allowing a more significant spatial analysis to be addressed. Secondly, general linear image processing frameworks are introduced in the GAN approach, using concepts of abstract linear algebra, so as to develop operators that are consistent with the physical and/or physiological settings of the image to be processed. In this paper, the GANIP approach is more particularly studied in the context of Mathematical Morphology (MM). The structuring elements, required for MM, are substituted by GAN-based structuring elements, fitting to the local contextual details of the studied image. The resulting transforms perform a relevant spatially-adaptive image processing, in an intrinsic manner, that is to say without a priori knowledge needed about the image structures. Moreover, in several important and practical cases, the adaptive morphological operators are connected, which is an overwhelming advantage compared to the usual ones that fail to this property.

Curved wavelet transform for image coding

Abstract: The conventional two-dimensional wavelet transform used in existing image coders is usually performed through one-dimensional (1-D) filtering in the vertical and horizontal directions, which cannot efficiently represent edges and lines in images. The curved wavelet transform presented in this paper is carried out by applying 1-D filters along curves, rather than being restricted to vertical and horizontal straight lines. The curves are determined based on image content and are usually parallel to edges and lines in the image to be coded. The pixels along these curves can be well represented by a small number of wavelet coefficients. The curved wavelet transform is used to construct a new image coder. The code-stream syntax of the new coder is the same as that of JPEG2000, except that a new marker segment is added to the tile headers. Results of image coding and subjective quality assessment show that the new image coder performs better than, or as well as, JPEG2000. It is particularly efficient for images that contain sharp edges and can provide a PSNR gain of up to 1.67 dB for natural images compared with JPEG2000.

Adaptive variable block transform system, medium, and method

Abstract: A variable block transform system, medium, and a system, medium, and method for video encoding/decoding using the variable block transform. The system includes a transform block size determination unit that determines the transform block size for components of an input video based on a format, defining the components, of the input video or characteristics of the components, and a transform coding unit that performs transform coding on each of the color components of the input video according to the determined transform block sizes and outputs transform coefficients.

Image sensing apparatus and method for synthesizing a composite image

Abstract: A composite image having a natural appearance is obtained when a synthesis target image is combined with a background image. By photographing a subject under different photographic conditions, a plurality of synthesis target images are obtained and the resulting image data is stored beforehand in a synthesis target image memory. A background image is acquired by photography and a suitable synthesis target image to be combined with the background image is selected by a circuit which searches synthesis target images. A color correction is applied to the selected synthesis target image by an image processing circuit and the synthesis target image following the color correction is combined with the background image. Since a synthesis target image suitable for combination with a background image is selected and then is subjected to a color correction and image synthesis processing, a composite image having a natural appearance is obtained.

Image Adaptation With Target Size, Quality and Resolution Constraints

Abstract: A computer-implemented method for image adaptation includes accepting a digitally-represented input image and a target size requirement. The input image is modified by optimally determining at least one of a resolution of the input image and a quality of the input image, the quality defining an amount of information allocated to represent each pixel value of the input image, so as to produce a compressed output image meeting the target size requirement.

Image display apparatus and image adjusting method

Abstract: An image display apparatus includes: an image signal processing unit which adjusts an input grayscale values included in an input image signal according to a predetermined grayscale characteristic; a display unit which displays an image based on an image signal included in an output grayscale value adjusted by the image signal processing unit; and a grayscale characteristic changing unit which changes a correlation between the input and output grayscale values defined based on the grayscale characteristic.

Image Processing Method, Image Processing Program, and Image Processing Device

Abstract: There is provided an image processing method for creating a fusion image with automatic and high superposition accuracy. The image processing method includes: (a) a voxel normalization step for generating a first normalized 3D image corresponding to a first 3D image and a second normalized 3D image corresponding to a second 3D image by making the voxel size and the voxel quantity the first 3D image based on a plurality of first tomograms obtained from an arbitrary portion of an examinee identical to those of the second 3D image based on a plurality of second tomograms obtained from the same portion in the valid field of view; and (b) a fusion image generation step for generating a fusion image by using the first normalized 3D image and the second normalized 3D image.

Image processing device, image processing method, program thereof, recording medium containing the program, and imaging device

Abstract: Provided are an image processing device, an image processing method, a program thereof, a recording medium containing the program, and an imaging device for processing image data obtained by capturing an optical image from an object via an imaging optical unit giving a distortion and containing the distortion of the imaging optical unit. A data output unit (13d) outputs image data on the display image based on the display mode by using an object image capable of identifying the selection region indicating a part of the field of view expressed by the image data and the image of the selection region distortion-corrected. The display mode setting unit (13c) sets the display mode. A control unit (13e) modifies the first display mode not using the object image capable of identifying the selection region as the display image to the second display mode using the object image capable of identifying the selection region as the display image when the selection region is switched.

Image processing apparatus, image processing system, and image processing program storage medium

Abstract: An image processing apparatus comprises an image data obtaining section that obtains image data, an image analyzing section that analyzes an image represented by the image data obtained by the image data obtaining section, an image processing section that applies image processing to the image data obtained by the image data obtaining section in accordance with an analyzing result analyzed by the image analyzing section and a processing parameter for introducing processing contents from the analyzing result, and a parameter adjusting section that adjusts, prior to the image processing by the image processing section, the processing parameter in accordance with an operation.

Method and system for image processing

Abstract: A method for image processing in a computerized system reduces the amount of memory required for image processing and produces a layered effect which permits complex manipulation such as scaling and rotation without long delay, while allowing earlier versions of the visual image to be recalled. The method involves pre-processing, image editing and raster image processing.

Image pickup device, image processor and image processing method

Abstract: PROBLEM TO BE SOLVED: To add out-of-focus to an image in a simple configuration about an obtained image. SOLUTION: An image formed by an optical system is picked up by an image pickup element, a defocus amount distribution in the picked-up image is detected, and processing based on the defocus amount distribution is applied to image data. COPYRIGHT: (C)2008,JPO&INPIT

Image processing methods, image processing systems, and articles of manufacture

Abstract: Image processing methods, image processing systems, and articles of manufacture are described. According to one aspect, an image processing method includes defining an image dimension corresponding to a common size of data content of a plurality of images which are associated with one another, determining a plurality of image boundaries individually corresponding to a size of the data content of a respective one of the images, comparing individual ones of the image boundaries with respect to the image dimension providing difference information for respective ones of the images and indicative of differences of the respective image boundaries with respect to the image dimension, and adjusting the images using respective difference information corresponding to respective ones of the images.

Image processing method, image processing apparatus, and image enlarging method

Abstract: An interpolated image obtained by enlarging and interpolating an image (IN) is subjected to predetermined vector transformation to calculate an image feature vector. Also, a characteristic of a subject is obtained to calculate a physical characteristic parameter of the interpolated image. The physical characteristic parameter is used to transform the image feature vector to sharpen the interpolated image. The transformed image feature vector is subjected to transformation inverse to the predetermined vector transformation to generate an enlarged image (ELI).

Image processing method, image processing apparatus, program and recording medium

Abstract: An image processing apparatus is provided. The image processing apparatus converts moving image data including plural first image data of a first resolution into moving image data including plural second image data of a second resolution. The apparatus generates position alignment data between the target first image data and another first image data other than the target first image data; aligns candidate image data having the second resolution corresponding to the target first image data with the other first image data according to the position alignment data generated; updates the candidate image data to minimize a first difference between the other first image data and the candidate image data position-aligned; and executes the aligning and the updating at least one time, and using the candidate image data having the difference equal to or smaller than a reference value, as the second image data corresponding to the target first image data.

Digital Image Scrambling Technology Based on the Symmetry of Arnold Transform

Abstract: An improved digital image scrambling method based on Arnold transform is proposed. The method can be used for the rectangle image by splitting rectangle image into several square images. Furthermore, a pretreatment is added to speeding up the process and enhancing the scrambling effect. The recovering of the scrambled image depends on the reverse Arnold transform that has the same cycle times with the Arnold transform. The recovering is lossless and need not calculating the period of the Arnold transform. Finally, experimental results show the robustness of the method.

Wavelet-hough transform with applications in edge and target detections

Abstract: In computer vision and image processing, edge detection concerns the localization of significant variations of the grey level image and the identification of the physical phenomena that originated them. It is difficult to design a general edge detection algorithm which performs well in many contexts and captures the requirements of subsequent processing stages. Consequently, over the history of digital image processing, a variety of edge detectors have been devised which differ in their mathematical and algorithmic properties. In this paper, we briefly describe some existing edge detectors. We investigate the wavelet transform with direction which is related to the Canny and Marr–Hildreth's edge detectors. This wavelet transform has a remarkable feature that plays an important role in image processing applications. We discuss its applications to edge and target detections. The direction effect enables the wavelets to analyze the directional features of images. Algorithms and experiments for edge and target detections have been developed based on the theory. And, very promising results have been shown in image processing.

SAR image formation with azimuth interpolation after azimuth transform

Abstract: Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.

Image Contrast Enhancement by Contourlet Transform

Abstract: We propose a new method for image contrast enhancement, based on a recently introduced 2D directional non-separable transform known as contourlet transform. Conventional 2D wavelet transform is separable and thus can not sparsely represent non-separable structures of the image, such as directional curves. The directionality feature of contourlet transform makes it a good choice for representation of curves and edges in the image. In this paper, a new enhancement function is proposed to enhance the edges by contourlet transform. The method is also compared with two usual contrast enhancement methods, histogram equalization and wavelet based contrast enhancement. It is shown that the contrast enhancement method based on contourlet transform is superior to both histogram equalization and the method based on wavelet transform, in both enhancement of fine structures in the image and denoising.

Robust feature extraction for color and grayscale images

Abstract: Systems, methods and program products for converting a first image to an intensity image using principal components analysis where the intensity image is based on a first principal component. The intensity image is analyzed to identify a plurality of scale invariant features in the intensity image, each identified feature associated with a score. An adaptive threshold is applied to the identified features to establish a set of features for the first image.

The contourlet transform for image fusion

Abstract: In this paper, we introduce a new image fusion method based on the contourlet transform. Firstly, the problem that wavelet transform could not efficiently represent the singularity of linear/curve in image processing is analyzed. Secondly, the principal of Contourlet and its good performance in expressing the singularity of two or higher dimensional are studied. Finally, the feasibility of image fusion using contourlet transform is discussed in detail. A new fusion method based on Contourlet transform and the fusion framework are proposed. The transform coefficients structure and the fusion procedure are given in detail in this paper. Experiments show that the proposed algorithm works better in preserving the edge and texture information than the wavelet transform method and the Laplacian pyramid methods do in image fusion.

Image enhancement by using directional wavelet transform

Abstract: The purpose of this paper is to introduce a novel image enhancement technique by using directional wavelet transform. Directional wavelet transform decomposes an image into four-dimensional space which augments the image by the scale and directional information. We show the directional information significantly improves image enhancement in noisy images in comparison with the classical techniques. Image enhancement is based on the multiscale singularity detection with an adaptive threshold whose value is calculated via maximum entropy measure. The proposed technique was tested on synthetic images at different signal-to-noise ratios and clinical images

Lane recognition apparatus

Abstract: A lane recognition apparatus that recognizes a lane from an input image sequence captured from a visual sensor mounted on a vehicle at a fixed time interval, includes a time series smoothing part for generating a smoothed feature image based on a feature image extracted from the input image sequence so that a dotted line lane boundary describes a linear locus over time, a gradient image generation part for generating a gradient image by estimating a feature value gradient at each pixel position of the smoothed feature image, and a Hough transform part for performing Hough transform on the gradient image and detecting lines of edges in the smoothed feature image.

Three-Dimensional Image Processing System Rendering Images by Partially Decompressing Compressed Image Data Set

Abstract: A method of three-dimensional image processing includes storing a set of compressed image data in a memory, the image data usable for creating three-dimensional images, identifying and decoding portions of the set of compressed image data stored in the memory based on requests sequentially issued by an image processing engine according to a progress of image processing, and providing the decoded portions of the set of compressed image data to the image processing engine.

Image pick-up apparatus, image pick-up program, and image processing program

Abstract: An image pick-up apparatus is disclosed which allows a reduction in degradation of images associated with a changed image magnification due to movements in a focus direction during image pick-up operation. The image pick-up apparatus has an image pick-up controller which performs a plurality of image pick-up operations for producing a single image and performs focus adjustment operation before each of the image pick-up operations to produce a first plurality of images, and an information producer which produces information on an image magnification of each of the first plurality of images. The image-pickup apparatus also has an image producer which produces a second plurality of images based on the first plurality of images and the information on the image magnification, and an image combiner which combines the second plurality of images to produce a single image.

Pointwise shape-adaptive DCT for high-quality deblocking of compressed color images

Abstract: We present an high-quality image deblocking algorithm based on the shape-adaptive DCT (SA-DCT) [20, 21]. The SA-DCT is a low-complexity transform which can be computed on a support of arbitrary shape. This transform has been adopted by the MPEG-4 standard [13] and it is found implemented in modern video hardware.