Abstract: A plurality of pieces of image data processed by a preprocessed circuit are sequentially received and at least one representative image is selected from among the plurality of pieces of image data by a representative image selection circuit. For example, one piece of image data out of every 250 pieces of image data is selected from among 1000 pieces of acquired image data to select four pieces of image data as representative images. An irradiated area extraction circuit extracts X-ray irradiated areas of the representative images. A reconstruction area determination circuit determines a CT reconstruction area on the basis of the X-ray irradiated areas. The reconstruction circuit reconstructs CT images from all or part of the acquired image data on the basis of the CT reconstruction area.

Abstract: In a radiation image processing apparatus and method, body movement information of a subject to be inspected is extracted during CT scanning. It is then determined whether or not a repeat radiograph is required based on the body movement information of the subject. If it is determined that a repeat radiograph is not required, a CT image is reconstructed from projection images. If it is determined that a repeat radiograph is required, the need for a repeat radiograph is instructed.

Abstract: It is an object to enable an irradiation field to be accurately extracted. An irradiation field extracting method of extracting an irradiation field from a radiation image is constructed by a step of extracting characteristic points in the radiation image by using geometric patterns for detecting an irradiation field edge and a step of detecting an edge portion of the irradiation field on the basis of the characteristic points.

Abstract: An object of this invention is to efficiently attain noise removal. In order to achieve the object, the discrete wavelet transforms of an input image are computed to output wavelet coefficients of respective subbands (S301). Appropriate threshold values are respectively set for subbands HL, LH, and HH indicating high-frequency components (S302a, S302b, S302c). The wavelet coefficients of the subbands HL, LH, and HH then undergo threshold value processes using the set threshold values for the respective subbands (S303a, S303b, S303c). Pixels to be processed in a coefficient conversion process are determined based on the threshold value processing results of the respective subbands (S304). The wavelet coefficients of the respective subbands corresponding to the pixels to be processed determined in step S304 undergo coefficient conversion (S305), and the converted transformation coefficients undergo inverse discrete wavelet transformation, thus reconstructing and outputting a noise-removed image (S306).

Abstract: An object of this invention is to efficiently attain noise removal. In order to achieve the object, the discrete wavelet transforms of an input image are computed to output wavelet coefficients of respective subbands (S301). Appropriate threshold values are respectively set for subbands HL, LH, and HH indicating high-frequency components (S302a, S302b, S302c). The wavelet coefficients of the subbands HL, LH, and HH then undergo threshold value processes using the set threshold values for the respective subbands (S303a, S303b, S303c). Pixels to be processed in a coefficient conversion process are determined based on the threshold value processing results of the respective subbands (S304). The wavelet coefficients of the respective subbands corresponding to the pixels to be processed determined in step S304 undergo coefficient conversion (S305), and the converted transformation coefficients undergo inverse discrete wavelet transformation, thus reconstructing and outputting a noise-removed image (S306).

Abstract: When stereoscopic video data is distributed through a network, some terminal cannot process the distributed stereoscopic video data because the format of the data does not correspond to the terminal. Likewise, when video data are input from a plurality of types of cameras with different stereoscopic video data formats, data of an incompatible format cannot be processed. In order to prevent this problem, there is provided a stereoscopic video apparatus which inputs stereoscopic video data, converts the format of the input stereoscopic video data into a format suitable to output operation, and outputs the converted stereoscopic video data to a network.

Abstract: When stereoscopic video data is distributed through a network, some terminal cannot process the distributed stereoscopic video data because the format of the data does not correspond to the terminal. Likewise, when video data are input from a plurality of types of cameras with different stereoscopic video data formats, data of an incompatible format cannot be processed. In order to prevent this problem, there is provided a stereoscopic video apparatus which inputs stereoscopic video data, converts the format of the input stereoscopic video data into a format suitable to output operation, and outputs the converted stereoscopic video data to a network.

Abstract: An image processing apparatus or an image processing method is arranged to input image data obtained by an image pickup device and an image pickup parameter of the image pickup device used in obtaining the image data, to make a comparison between the image pickup parameter for a target image and the image pickup parameter for another image, and to decide whether or not the target image differs from the other image, according to a result of the comparison.

Abstract: An object of this invention is to efficiently attain noise removal. In order to achieve the object, the discrete wavelet transforms of an input image are computed to output wavelet coefficients of respective subbands (S301). Appropriate threshold values are respectively set for subbands HL, LH, and HH indicating high-frequency components (S302a, S302b, S302c). The wavelet coefficients of the subbands HL, LH, and HH then undergo threshold value processes using the set threshold values for the respective subbands (S303a, S303b, S303c). Pixels to be processed in a coefficient conversion process are determined based on the threshold value processing results of the respective subbands (S304). The wavelet coefficients of the respective subbands corresponding to the pixels to be processed determined in step S304 undergo coefficient conversion (S305), and the converted transformation coefficients undergo inverse discrete wavelet transformation, thus reconstructing and outputting a noise-removed image (S306).

Abstract: In order to eliminate noise from an X-ray image by obtaining transform coefficients of a wavelet transform based upon information contained in tile-by-tile image data and obtaining image data based upon these transform coefficients, the entirety of a pre-processed original image is segmented into a plurality of tiles (S301). Wavelet transform coefficients of each tile obtained by segmentation are output (S302). Each tile is subjected to texture analysis and the results of analysis are output (S303). Next, a coefficient conversion is applied to the wavelet transform coefficients of each tile based upon the results of analysis (S304). High-frequency components among the transform coefficients are subjected to coefficient conversion. Next, an inverse discrete wavelet transform is applied to the wavelet transform coefficients of each area that has undergone conversion, whereby an image from which noise has been eliminated is output (S306).

Abstract: Obtains an image from which noise is removed upon compressing or decoding and displaying an image containing noise. To accomplish this, a subband to which a wavelet transform coefficient of interest belongs is checked upon entropy decoding, and when the coefficient belongs to a subband other than LL, decoding is aborted at a predetermined lower-limit bit plane, and all bits contained in bit planes from the lower-limit bit plane to the least significant bit plane are set at zero.

Abstract: It is an object to enable an irradiation field to be accurately extracted. An irradiation field extracting method of extracting an irradiation field from a radiation image is constructed by a step of extracting characteristic points in the radiation image by using geometric patterns for detecting an irradiation field edge and a step of detecting an edge portion of the irradiation field on the basis of the characteristic points.