Showing papers by "Tomoo Mitsunaga published in 2003"

Image processing apparatus and method, recording medium, and program

Abstract: In an image processing apparatus, a sensitivity compensation unit converts a color-and-sensitivity mosaic image into a color mosaic image A pixel-of-interest determination unit extracts local area information from the color mosaic image An edge-direction detector detects an edge of the local area A G-component computing unit performs weighted interpolation in the edge direction of the green (G) component associated with a pixel of interest A statistic computing unit computes statistic information of the local area A first or second R-and-B-component computing unit computes the red (R) and blue (B) components of the pixel of interest on the basis of the statistic information An inverse gamma conversion unit performs inverse gamma conversion of the red (R), green (G), and blue (B) components of the pixel of interest The present invention is applicable to, for example, a digital still camera

Image processing device and method

Abstract: The present invention relates to an image processing apparatus and a method, and in particular to an image processing apparatus and a method preferably applicable to conversion of a wide dynamic-range image having a dynamic range of pixel values wider than the normal one to a narrow dynamic-range image having a narrower dynamic range of pixel values, and to enhancement of contrast. In step S 1 , an input wide-DR luminance image of the current frame is converted into a narrow-DR luminance image based on the intermediate information calculated for the previous frame's wide-DR luminance image. In step S 2 , the stored intermediate information of the previous frame is updated using the calculated intermediate information. In step S 3 , it is determined if there is any succeeding frame. If there is the succeeding frame, the process returns to step S 1 and processes thereafter are repeated. The present invention is applicable to a digital video camera and the like.

Apparatus and method for image processing, recording medium, and program

Abstract: PROBLEM TO BE SOLVED: To generate a wide DR color image from a color/sensitivity mosaic image with a smaller operation quantity than before while decreasing the number of frame memories etc., in use. SOLUTION: A sensitivity compensation part 63 converts the color/sensitivity mosaic image into a color mosaic image. An interest pixel determination part 61 extracts local area information from the color mosaic image. An edge direction detection part 66 detects an edge of the local area. A G component calculation part 67 performs weighted interpolation of the G component of a pixel of interest according to the edge direction. A statistic calculation part 69 calculates the statistic information of the local area. A first R and B component calculation part 70 or second R and B component calculation part 70 calculates the R and B components of the pixel of interest according to the statistic information. A reverse gamma conversion part 73 performs reverse gamma conversion of the R, G, and B components of the pixel of interest. The present invention is applicable to, for example, a digital still camera. COPYRIGHT: (C)2004,JPO&NCIPI

Image processor and image processing method

Abstract: PROBLEM TO BE SOLVED: To provide an image processor and an image processing method to be suitably used at the time of executing de-mosaic processing(color interpolation processing or simultaneous processing) to interpolate a plurality of colors into overall pixels, and to obtain a color image signal from a mosaic image signal obtained by using a color solid-state imaging element. SOLUTION: Four color array shown in the figure is configured by alternatively arranging R and B at the opposite angles with an alternative cycle by every pixel in the direction of upward slant to the right and in an alternative cycle by every two pixel in the direction of downward slant to the right. A rough interpolation processing part calculates a plurality of sets of the strength of a first color Cr which is the same as the color at the pixel position under consideration and the strength of a second color Ce based on a mosaic image extracted from such filter array. A statistic calculating part calculates statistic concerning the color distribution shape of the strength of Cr and the strength of Ce. A recursion arithmetic operation processing part calculates the Ce estimate of the pixel position under consideration based on the strength of the color Cr at the pixel position under consideration and the statistic of the color distribution shape. Thus, it is possible to obtain an output image with much higher picture quality by solving such two phenomena as color moire and false color generated due to the engineering of a chrominance signal. This invention may be applied to a digital still camera. COPYRIGHT: (C)2005,JPO&NCIPI

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

Abstract: PROBLEM TO BE SOLVED: To reduce the capacity of a memory to be used and an operation quantity, to easily form into hardware, and to emphasize the contrast of an image subjected to proper gradation compression. SOLUTION: In a step S21, the luminance of a wide DR image L is subjected to logarithmic conversion. In a step S22, a logarithmic tone curve correction image logL c is generated. In step S23, a logarithmic reduction image logL cl is generated, and luminance logL cl (p) of a pixel of a logarithmic smoothed image is further calculated by interpolation operation. In step S24, a gain value g(p) is calculated for each pixel position. In a step S25, luminance logL u (p) of a pixel of a logarithmic gradation compressed image logL u (p) is calculated. In a step S26, the luminance logL u (p) is subjected to logarithmic inverse conversion. This apparatus is applicable to an image pickup device such as a digital video camera, and a reproducing device such as a display and a printer. COPYRIGHT: (C)2004,JPO&NCIPI

Device and method for processing image, and program

Abstract: PROBLEM TO BE SOLVED: To suppress generation of a false color and deterioration in resolution, and to interpolate a color constituent to all pixels when performing color interpolation processing of thinned-out mosaic signals. SOLUTION: At a G, E interpolation processor 262, adjacent G's in the right and left are used for interpolating G at a pixel position at which G in a line does not exist, in the line in which G exists, and adjacent E's in the right and left are interpolated at a pixel position with no E in a line, in the line in which E exists. At an all-color interpolation processing section 264, a luminance signal L and the mosaic signal M are used for calculating an interpolation value C of R, G, B, E at a noted pixel position. A G+E generation processing section 263, a new color constituent G+E is generated, based on the mosaic signal M. At an all-color interpolation processor 265, an interpolation value C' of R, G, B, E is calculated at a noted pixel position, based on the constituent G+E and the mosaic signal M. At a composition processor 266, C and C' are composed for calculating a final all-color interpolation signal. The device and the method is applied to digital cameras. COPYRIGHT: (C)2005,JPO&NCIPI

High dynamic range imaging: Spatially varying pixel exposures

Abstract: While real scenes produce a wide range of brightness variations, vision systems use low dynamic range image detectors that typically provide 8 bits of brightness data at each pixel. The resulting low quality images greatly limit what vision can accomplish today. This paper proposes a very simple method for significantly enhancing the dynamic range of virtually any imaging system. The basic principle is to simultaneously sample the spatial and exposure dimensions of image irradiance. One of several ways to achieve this is by placing an optical mask adjacent to a conventional image detector array. The mask has a pattern with spatially varying transmittance, thereby giving adjacent pixels on the detector different exposures to the scene. The captured image is mapped to a high dynamic range image using an efficient image reconstruction algorithm. The end result is an imaging system that can measure a very wide range of scene radiance and produce a substantially larger number of brightness levels, with a slight reduction in spatial resolution. We conclude with several examples of high dynamic range images computed using spatially varying pixel exposures.