Abstract: A power supply device with enhanced safety is provided. A power supply device (100) includes secondary battery cells (1) each including a positive electrode (2) including a safety valve on one end surface of each cell, a battery holder holding the secondary battery cells (1) each including the positive electrode (2) on the one end surface thereof, and a housing (20) having a bottom surface (22), a top surface (23), and an inner space which accommodates the battery holder therein. The battery holder holds the secondary battery cells (1) upright in parallel to one another such that the positive electrode (2) on the one end surface of each cell (1) is directed vertically downward. In the housing (20), the battery holder retains the positive electrode (2) of each cell (1) spaced apart from the bottom surface (22) across a first space (SP1).

Abstract: An information processing apparatus (100) includes a generation unit (132), a conversion unit (133), an evaluation unit (134), an image analysis unit (135), and a determination unit (138). The generation unit (132) performs supervised learning using first image data and teacher data and generates an image conversion model. The conversion unit (133) generates converted data from the second image data using the image conversion model. The evaluation unit (134) evaluates the converted data. The image analysis unit (135) analyzes second image data corresponding to the converted data, evaluation of which by the evaluation unit (134) is lower than a predetermined standard. The determination unit (138) determines, based on an analysis result by the image analysis unit (135), a photographing environment of photographing performed to acquire teacher data.

Abstract: The present technology relates to an image processing device, an image processing method, a learning device, a generation method, and a program for enabling generation of an image in which an appropriate texture is expressed in each region. An image processing device according to the present technology generates a control signal indicating the texture of each region in an output image as an inference result on the basis of an input image to be processed, inputs the input image to an inference model, and infers the output image in which each region has a texture indicated by the control signal, the inference model being obtained by performing learning based on a trainee image and a training image, the trainee image being generated by performing predetermined image processing on the training image, the texture of each region being expressed by a texture label in the training image. The present technology can be applied to various kinds of devices that handle images, such as TV sets, cameras, and smartphones.

Abstract: The present disclosure relates to an image processing apparatus and a method which enable a sense of quality as if there were a real object to be more favorably reproduced. A characteristic control unit determines processing contents for controlling the sense of quality, for example, changing an image quality, adjusting a reflection characteristic, or changing a shape, on the basis of a physical characteristic parameter from a characteristic information integration unit and device information from a device information analyzer. The characteristic control unit supplies information on the determined processing contents to an image composition unit and an additional-information generation unit and causes the image composition unit and the additional-information generation unit to perform sense-of-quality control. That is, in the image processing apparatus, more realistic visual expression becomes possible with an image output of one device as well as an output other than an image from another device.

Abstract: The present disclosure relates to an image processing apparatus and method capable of reproducing a material feel just like a real thing is there. A reflection characteristic estimation unit estimates and analyzes, from a supplied input image, a reflection characteristic of the subject as a characteristic of a subject. The reflection characteristic estimation unit supplies a specular reflection component as a reflection characteristic estimation result to a characteristic information integrating unit and a highlight area detection unit as an image estimation information. The highlight area detection unit performs highlight area detection in parallel to processing with the reflection characteristic estimation unit by using the specular reflection component as the reflection characteristic estimation result from the reflection characteristic estimation unit, and supplies the highlight area detection result to a characteristic information integrating unit as the image estimation information.

Abstract: The present disclosure relates to an image processing apparatus and method capable of reproducing texture as if objects are actually present. An operation environment information analysis unit acquires and analyzes user's operation environment information for an image while the image is being displayed. The operation environment information analysis unit supplies the analyzed operation environment information as operation environment parameters to a property control unit. The property control unit causes an image combination unit to conduct texture control depending on visual environment parameters or operation environment parameters, thereby optimizing the texture control. The present disclosure is applicable to image processing apparatuses, for example.

Abstract: The present disclosure relates to image processing apparatus and method which enable a sense of quality as if there were a real object to be more favorably reproduced. A characteristic control unit determines processing contents for controlling the sense of quality, for example, changing an image quality, adjusting a reflection characteristic, or changing a shape, on the basis of a physical characteristic parameter from a characteristic information integration unit and device information from a device information analyzer. The characteristic control unit supplies information on the determined processing contents to an image composition unit and an additional-information generation unit and causes the image composition unit and the additional-information generation unit to perform sense-of-quality control. That is, in the image processing apparatus, more realistic visual expression becomes possible with an image output of one device as well as an output other than an image from another device.

Abstract: The present disclosure relates to an image processing apparatus and method capable of reproducing a material feel just like a real thing is there. A reflection characteristic estimation unit estimates and analyzes, from a supplied input image, a reflection characteristic of the subject as a characteristic of a subject. The reflection characteristic estimation unit supplies a specular reflection component as a reflection characteristic estimation result to a characteristic information integrating unit and a highlight area detection unit as an image estimation information. The highlight area detection unit performs highlight area detection in parallel to processing with the reflection characteristic estimation unit by using the specular reflection component as the reflection characteristic estimation result from the reflection characteristic estimation unit, and supplies the highlight area detection result to a characteristic information integrating unit as the image estimation information.

Abstract: The present disclosure relates to an image processing apparatus and method capable of reproducing texture as if objects are actually present. An operation environment information analysis unit acquires and analyzes user's operation environment information for an image while the image is being displayed. The operation environment information analysis unit supplies the analyzed operation environment information as operation environment parameters to a property control unit. The property control unit causes an image combination unit to conduct texture control depending on visual environment parameters or operation environment parameters, thereby optimizing the texture control. The present disclosure is applicable to image processing apparatuses, for example.

Abstract: Disclosed herein is an image processor, including: a detecting portion detecting a composition of an input image; a first generating portion generating first information in accordance with an intensity of image processing based on the composition detected by the detecting portion is controlled; a second generating portion detecting a flat portion in which a change in pixel values corresponding to the input image is small, and generating second information in accordance with which an intensity of image processing for the flat portion is controlled; a third generating portion detecting a foreground portion of the input image, and generating third information in accordance with which an intensity of image processing for the foreground portion is controlled; and an image processing portion executing image processing in accordance with an intensity based on the first information, the second information, and the third information.

Abstract: Disclosed herein is an image processing apparatus, including a noise detection section, a scaling section, an adjustment signal production section, and a correction section. The noise detection section is adapted to detect block noise based on an input image signal in a compression coded form and output noise information indicative of the detected block noise. The scaling section is adapted to carry out a scaling process for carrying out enlargement or reduction of an image indicated by the input image signal for the input image signal and output scaling information indicative of an enlargement ratio or a reduction ratio. The adjustment signal production section is adapted to output an adjustment signal indicative a degree of correction based on the noise information and the scaling information. The correction section is adapted to correct the image signal for which the scaling process is carried out based on the adjustment signal.

Abstract: An image processing apparatus according to an embodiment of the present invention includes a correction interval setting unit for setting a correction interval; a correction interval dividing unit for dividing the correction interval into a black side interval and a white side interval; histogram calculating units for calculating a total number of luminance histograms of the black side interval and the white side interval, respectively; gain setting units for setting gains of a ? curve for raising the luminance and a ? curve for lowering the luminance, respectively; gamma curve generating units for generating a gamma curve for raising the luminance and a gamma curve for lowering the luminance, respectively; a gamma curve combining unit for combining the gamma curve for raising the luminance and the gamma curve for lowering the luminance; and a luminance conversion unit for performing the luminance conversion process using the combined gamma curve.

Abstract: An image correction circuit capable of easily achieving adaptive color correction on the basis of a luminance correction amount is provided. An image correction circuit includes: a luminance correction section for performing luminance correction on input image data; and a color correction section for performing adaptive color correction on input image data on the basis of the following formula (1): Cout?Cin×[1+M×(?Y/L)]??(1) where Cout represents a chrominance signal after color correction, Cin represents a chrominance signal before color correction, M represents an adaptive color correction magnitude which is a fixed positive value, ?Y represents the total amount of luminance correction by the luminance correction section, L represents a fixed positive value satisfying L<(Ymax/2), and Ymax represents maximum luminance of input image data.

Abstract: An image processing apparatus according to an embodiment of the present invention includes a correction interval setting unit for setting a correction interval; a correction interval dividing unit for dividing the correction interval into a black side interval and a white side interval; histogram calculating units for calculating a total number of luminance histograms of the black side interval and the white side interval, respectively; gain setting units for setting gains of a ? curve for raising the luminance and a ? curve for lowering the luminance, respectively; gamma curve generating units for generating a gamma curve for raising the luminance and a gamma curve for lowering the luminance, respectively; a gamma curve combining unit for combining the gamma curve for raising the luminance and the gamma curve for lowering the luminance; and a luminance conversion unit for performing the luminance conversion process using the combined gamma curve.

Abstract: An image correction circuit capable of easily achieving adaptive color correction on the basis of a luminance correction amount is provided. An image correction circuit includes: a luminance correction means for performing luminance correction on input image data; and a color correction means for performing adaptive color correction on input image data on the basis of the following formula (1): Cout?Cin×[1+M×(? Y/L)] ??(1) where Cout represents a chrominance signal after color correction, Cin represents a chrominance signal before color correction, M represents an adaptive color correction magnitude which is a fixed positive value, ? Y represents the total amount of luminance correction by the luminance correction means, L represents a fixed positive value satisfying L<(Ymax/2), and Ymax represents maximum luminance of input image data.