An image converting device includes; a downscaling unit which downscales a two-dimensional image to generate at least one downscaling image, a feature map generating unit which extracts feature information from the downscaling image to generate a feature map, wherein the feature map includes a plurality of objects, an object segmentation unit which divides the plurality of objects, an object order determining unit which determines a depth order of the plurality of objects, and adds a first weight value to an object having the shallowest depth among the plurality of objects, and a visual attention calculating unit which generates a low-level attention map based on visual attention of the feature map.

Image converting device and three-dimensional image display device including the same

Disclosed are apparatus and methods for denoising a video stream of a camera. A current frame of the video stream and a temporally adjacent frame of the video stream that has been previously spatially and temporally denoised are obtained. The current frame is first spatially denoised, while preserving edges in such current frame to generate a plurality of spatially denoised pixels for the current frame. A particular pixel of the current frame is then both spatially and temporally denoised based on a weighted averaging of the particular pixel's associated spatially denoised pixel from the current frame and a plurality of pixels from the temporally adjacent frame that have already been spatially and temporally denoised.

Systems and Methods for Reducing Noise in Video Streams

A radiographic apparatus which includes an X-ray irradiation unit which irradiates X-rays and an X-ray detection unit which detects an X-ray image of an object irradiated by the X-ray irradiation unit includes a first defect detection unit which detects, as a position-dependent defect, a pixel, of X-ray images, whose pixel value is always abnormal, and acquires position information of the defect in the X-ray image, a second defect detection unit which detects, as a defect, a pixel, of the X-ray images, which temporarily becomes abnormal dependent on the lapse of time, and a determination unit which determines a correction method for correcting the pixel value of the pixel in which the abnormality is detected by the second defect detection unit, based on the information indicating the imaging condition.

Radiographic apparatus and control method for the same

An image processing apparatus includes: a pixel difference calculator for calculating a difference value between each first pixel of a previous image and a second pixel of a present image and at a position corresponding to said each first pixel, and outputting a plurality of pixel differences; a counter counting a number of positive pixel differences and a number of negative pixel differences in the pixel differences of a sampling window; a motion level determining unit calculating a motion level of a pixel in the sampling window according to the numbers of the positive and negative pixel differences; a blending value determining unit determining a blending value according to the motion level; and an output unit adding together weights of the present and previous images according to the blending value to generate and output an output image An image processing method is also disclosed

Image Processing Apparatus and Method

Provided is an image processing apparatus, medium, and method. The image processing apparatus may include a first calculator and a second calculator. The first calculator may calculate a first weight of a first frame depth value of a first pixel of a depth image and a second weight of a second frame depth value of the first pixel, based on an obtainment time difference between the first frame depth value of the first pixel and the second frame depth value of the first pixel among a plurality of frame depth values of the first pixel. The second calculator may determine a corrected first frame depth value of the first pixel using a linear sum that is calculated by applying the first weight to the first frame depth value of the first pixel, and by applying the second weight to the second frame depth value of the first pixel.

Image processing apparatus, medium, and method

A method and apparatus are provided for eliminating image noise to remove spatial-temporal noise and improve visibility. The method includes extracting a spatial-temporal noise level of neighbor pixels around a current pixel, filtering noise of the current pixel by applying a weight to spatial-temporal pixels around the current pixel based on the extracted spatial-temporal noise level, and applying a weight to the noise-filtered pixel and a boosted-up pixel based on an edge intensity and summing the weight-applied pixels. The spatial-temporal noise level is extracted based on spatial-temporal information of neighbor pixels around a current pixel in a current frame and spatial-temporal information of neighbor pixels around a current pixel in a previous frame.

Method of and apparatus for eliminating image noise

A method and an apparatus for removing an image noise are provided to inhibit the noise generated at the visually sensitive intermediate gradation by means of a visual model, thereby enhancing the visibility. A noise degree extraction member(100) extracts the degree of temporal and spatial noise of peripheral pixels of the present pixel on the basis of the temporal and spatial information on peripheral pixels of pixels of the present and previous frames. A temporal-spatial noise removing member(160) weights the temporal and spatial pixel at the circumference of the present pixel according to the degree of the noise extracted from the noise degree extraction member and filters the noise of the present pixel. A boundary improving member(170) sums the noise filtered pixel and the boost-up pixel by applying the weight value according to the boundary intensity. The noise degree extraction member includes a boundary parameter extraction member.

Hwang Won Kyu

Papers

Method of and apparatus for eliminating image noise

Method and apparatus for eliminating image noise