Abstract:
Provided is a pattern generation device for generating a sampling pattern that could make it possible to improve the efficiency of image processing, including the processing of sampled blocks. A pattern generation device as in one embodiment of the present invention is provided with: a main generating means for generating a sampling pattern which is a pattern of positions of sampling points in an image, the sampling points indicating blocks to be used in image processing of the respective blocks, and the sampling pattern generated so that the numbers of sampling points in a plurality of rows in the sampling pattern are each equal to a reference value; and an output control means for performing a control for outputting a main sampling pattern, which is the sampling pattern generated by the main generating means.
Abstract:
When performing noise removal of an image signal by applying the background art, there is a case where a filter coefficient that causes an edge constituting the image to become blurred against expectation due to the influence of noise in the image signal is set. The methods to solve this problem include a method for calculating a wide range of image feature values needed for correction of the filter coefficient, but this method has the problem that it requires a significant amount of calculation, thus increasing the calculation cost. To solve the above problem, the present invention is provided with an image signal input means, a wavelet transformation means, a first structure/texture separating means, a texture component degenerating means, a first combining means, an inverse wavelet transformation means, and a second structure/texture separating means. The present invention is further provided with a second texture component degenerating means, a second combining means, and an image signal output means.
Abstract:
A video encoding device includes: pixel bit length increasing means for increasing a pixel bit length of an input image based on pixel bit length increase information; transform means for transforming output data of the pixel bit length increasing means; entropy encoding means for entropy-encoding output data of the transform means; non-compression encoding means for non-compression-encoding input data; multiplexed data selection means for selecting output data of the entropy encoding means or output data of the non-compression encoding means; and multiplexing means for multiplexing the pixel bit length increase information in a bitstream, wherein a pixel bit length of an image corresponding to the output data of the entropy encoding means and a pixel bit length of an image corresponding to the output data of the non-compression encoding means are different from each other.
Abstract:
Disclosed is an image processing method including: generating an initial denoised image with a reduced noise while preserving an edge in an input image; controlling an iterative operation performed based on energy defined in advance based on an initial residual component calculated from the input image and the initial denoised image; and separating the initial denoised image to a skeleton component and a residual component by the controlled iterative operation to generate the skeleton component as an output image.
Abstract:
The present invention is a method including: correcting difference between a pixel statistical value of a specific layer and a pixel statistical value of a layer that is wider than the specific layer using an edge information of a layer that is wider than the specific layer; correcting the pixel statistical value of the specific layer using post-correction difference and the pixel statistical value of layer that is wider than the specific layer; recorrecting the post-correction pixel statistical value of the specific layer using difference between a pre-correction pixel statistical value of the specific layer and the post-correction pixel statistical value of the specific layer and the edge information of a layer that is wider than the specific layer; and correcting the target pixel by repeating correction and recorrection until the layer reduces its range from the maximum range to the minimum range.
Abstract:
An information display apparatus includes: a collation unit that specifies a position of an object in an overhead image obtained by capturing an image of a region that includes the object before a disaster, based on a result of collating the overhead image with a section in a target image that includes a situation of the object after the disaster, the section satisfying a criterion for determining that an influence of the disaster is small; and a display unit that displays an image that includes the situation of the object and information by which the position of the object in the overhead image can be specified.
Abstract:
A video decoding device and method, including extracting PCM block size information including a threshold, from a bitstream, determining the threshold based on the extracted PCM block size information; parsing a PCM header from the bitstream with respect to an encoded block, only when said encoded block is prediction mode of intra prediction and a block size of said encoded block is equal to or greater than the determined threshold, controlling an entropy decoding process and a PCM decoding process based on the parsed PCM header; parsing transformed data of a prediction error data of an image in the bitstream; and PCM-decoding PCM data of the image in the bitstream, wherein the decoding performs the decoding operation based on the prediction mode being intra prediction and based on the block size of the encoded block being equal to or greater than the determined threshold.
Abstract:
In a video decoding device, a quantization step size decoding unit calculates a quantization step size that controls a granularity of the inverse quantization by, based on an image prediction, selectively using a mean value of at least a quantization step size assigned to a leftwardly adjacent neighboring image block already decoded and a quantization step size assigned to a upwardly adjacent neighboring image block already decoded or a quantization step size assigned to an image block decoded immediately before.
Abstract:
An image processing device 10 includes: a segmentation unit 21 that segments an input image 200 representing a result of observing an ocean surface region and a land surface region from overhead into ocean surface block images 211 and land surface block images 212, based on a segmentation criterion 210; a first determination unit 22 that determines a binarization criterion 220 for the ocean surface block images 211, based on a scattering model for electromagnetic waves in the ocean surface region; a second determination unit 23 that determines a binarization criterion 230 for the land surface block images 212, based on the binarization criterion 220 and a positional relationship between the ocean surface block images and the land surface block images; and a generation unit 25 that generates a land mask image 250 by performing binarization processing on the input image 200 based on the binarization criterion 220 and the binarization criterion 230. Consequently, the image processing device 10 improves the accuracy in generating the land mask image for differentiating between the ocean surface region and the land surface region in remote sensing technology.
Abstract:
An image processing method separates an input image into a skeleton component, and residual component. In the method a local variation amount, which is a variation amount between a target pixel and a pixel adjacent to the target pixel, is calculated; a skeleton component extraction filter weight is calculated based on the local variation amount; an image feature amount of a gradient direction of a pixel value around the target pixel, and an image feature amount of a gradient strength of the pixel value around the target pixel, are calculated; the skeleton component extraction filter weight is corrected based on these image feature amount; a skeleton component extraction filter coefficient is calculated based on the corrected skeleton component extraction filter weight; and the skeleton component is extracted by applying skeleton component extraction filtering to the target pixel using the calculated skeleton component extraction filter coefficient.