Abstract: Effective image correction processing for reducing flicker is executed according to characteristics of images, and an image to be displayed in a liquid crystal display apparatus is generated. Characteristic amount change rate data that is a change rate between a characteristic amount of a sample image and a characteristic amount of a sample image output to a liquid crystal display device is acquired in advance and stored in a storage unit. The correction parameter for reducing flicker is calculated on the basis of the characteristic amount of the image to be corrected and the characteristic amount change rate data of the sample images stored in the storage unit. The correction processing to which the calculated correction parameter has been applied is executed for the image to be corrected to generate a display image. As the characteristic amount, for example, the interframe luminance change amount, the interline luminance conversion amount, or the interframe motion vector is used.

Abstract: A transmittance estimation unit estimates a transmittance for each of regions from a captured image. The transmittance estimation unit estimates the transmittance for each pixel, using, for example, dark channel processing. A transmittance detection unit detects a transmittance of haze at the time of imaging of the captured image, using the transmittance estimated for each pixel by the transmittance estimation unit and depth information for each pixel. The transmittance detection unit detects the transmittance of the haze on the basis of, for example, a logarithm average value of the transmittances in the whole or a predetermined portion of the captured image, and an average value of depths indicated by the depth information.

Abstract: A coefficient calculator calculates a correlation coefficient representing a correlation between a normal frame, which is imaged in a state in which normal light is applied to a subject, and a special frame, which is imaged in a state in which special light is applied to the subject; and a processing unit that applies image processing to the special frame so that a part in which the correlation coefficient is high and a part in which the correlation coefficient is low are displayed differently in the special frame. Further provided are: a first determination unit that calculates, for each pixel or each area of the normal frame, a first determination value representing a probability that a predetermined site is imaged; and a second determination unit that calculates, for each pixel or each area of the special frame, a second determination value representing a probability that a predetermined site is imaged.

Abstract: Provided are an apparatus and a method that perform a process of improving the quality of a far-infrared image. An image processing apparatus includes: a first combination unit that receives a far-infrared image and multiple reference images obtained by capturing the same object as that of the far-infrared image and generates a first composite signal which is a composite signal of the multiple reference images; and a second combination unit that performs a process of combining the far-infrared image and the first composite signal to generate a quality-improved image of the far-infrared image. The reference images are, for example, a visible image and a near-infrared image. The first combination unit generates the first composite signal on the basis of a visible image-far-infrared image correlation amount and a near-infrared image-far-infrared image correlation amount.

Abstract: There is provided an apparatus and a method that perform a process of improving the quality of a low-quality image such as a far-infrared image. The apparatus includes an image correction unit that repeatedly performs an image correction process using a plurality of processing units in at least two stages. The image correction unit inputs a low-quality image to be corrected and a high-quality image which is a reference image. Each of the processing units in each stage performs a correction process for the low-quality image, using a class correspondence correction coefficient corresponding to a feature amount extracted from a degraded image of the high-quality image. A processing unit in a previous stage performs the correction process, using a class correspondence correction coefficient corresponding to a feature amount extracted from an image which has a higher degradation level than that in a processing unit in a subsequent stage.

Abstract: An apparatus and method are provided for generating a superimposed image of a visible light image and a fluorescence image having a noise level which substantially coincides with a noise level of the visible light image. A fluorescence image noise reduction unit executes noise reduction processing on a fluorescence image and generates a noise reduced fluorescence image, an image superimposing unit generates a superimposed image of a visible light image and a noise reduced fluorescence image according to a set superimposing rate, and a fluorescence image noise reduction intensity calculation unit calculates a noise reduction intensity which is applied to the noise reduction processing on the fluorescence image. Even when the superimposing rate is changed, a noise reduction intensity is calculated having a value which makes a noise level of the noise reduced fluorescence image substantially coincide with a noise level of the visible light image forming the superimposed image.

Abstract: Provided are an apparatus and a method for executing image quality enhancement processing on a fluorescence image. A fluorescence image and a visible light image are input and the image feature amount is extracted, so as to execute pixel value correction processing on the fluorescence image on the basis of a correction parameter determined in accordance with the feature amount. The correction parameter used for pixel value correction is determined by the correction parameter calculation unit on the basis of the feature amount. The image correction unit executes pixel value correction processing that applies the correction parameter determined by the correction parameter calculation unit. For example, blur mode information is obtained as a feature amount from a fluorescence image, and the image correction unit executes pixel value correction processing on the fluorescence image so as to reduce blur of the fluorescence image.

Abstract: Provided is a device and a method for executing image quality improvement processing of an infrared light image. Included are: a feature amount calculating unit for receiving an infrared light image and a visible light image and extracting a feature amount from at least one of the images; and an image correcting unit for executing pixel value correction processing on the infrared light image on the basis of a reference area and a correction parameter determined depending on the feature amount. Further included are: a tap selection unit for determining the reference area used for the pixel value correction on the basis of the feature amount; and a correction parameter calculating unit for determining the correction parameter used for the pixel value correction on the basis of the feature amount.

Abstract: [Object] To generate a color image with further improved image quality. [Solution] Provided is an image processing device including: an image acquisition unit that acquires a far-infrared image, a near-infrared image, and a visible light image in which a common imaged object is captured; and a generation unit that generates a color image by filtering filter taps including pixels of the far-infrared image, the near-infrared image, and the visible light image.

Abstract: The present disclosure relates to an image processing apparatus, an image processing method, and a program which can suppress degradation of image quality when power consumption of a display unit is reduced by reducing luminance of an image. A determining unit determines a reduction amount of luminance of a pixel based on characteristics of each pixel of an input image. A reducing unit reduces the luminance of the pixel of the input image by the reduction amount determined by the determining unit. The present disclosure can be applied to, for example, an image processing apparatus, or the like, which reduces luminance of a pixel based on characteristics of each pixel of an input image and displays the input image whose luminance is reduced.

Abstract: An image processing device includes a calculation unit which calculates a luminosity of an environmental light of an image for each region based on an overall average value which is an average value of the luminosity of all pixels forming the image of an object and region average values which are the average values of the luminosity of the pixels for each region that is obtained by dividing the image, and a generation unit which generates a virtual captured image which is an image of the object when the object is illuminated with light from a predetermined position based on the luminosity of the environmental light for each of the regions of the image that is calculated by the calculation unit and the image.

Abstract: An interpolation processing unit 31 performs an interpolation process of a decimated pixel in an image signal. A signal generation pixel determination unit 32 calculates a feature value of a pixel of interest from the image signal to which the interpolation process is performed by the interpolation processing unit 31, and determines whether the pixel of interest is a decimated pixel or a non-decimated pixel on the basis of the calculated feature value, and generates signal generation pixel determination information indicating a determination result. A signal generation control unit 34 performs control to stop signal generation operation of the pixel that is determined to be the decimated pixel by the signal generation pixel determination information generated by the signal generation pixel determination unit 32, at a time of subsequent generation of an image signal.

Abstract: An interpolation processing unit 31 performs an interpolation process of a decimated pixel in an image signal. A signal generation pixel determination unit 32 calculates a feature value of a pixel of interest from the image signal to which the interpolation process is performed by the interpolation processing unit 31, and determines whether the pixel of interest is a decimated pixel or a non-decimated pixel on the basis of the calculated feature value, and generates signal generation pixel determination information indicating a determination result. A signal generation control unit 34 performs control to stop signal generation operation of the pixel that is determined to be the decimated pixel by the signal generation pixel determination information generated by the signal generation pixel determination unit 32, at a time of subsequent generation of an image signal.

Abstract: [Object] To generate a color image with further improved image quality. [Solution] Provided is an image processing device including: an image acquisition unit that acquires a far-infrared image, a near-infrared image, and a visible light image in which a common imaged object is captured; and a generation unit that generates a color image by filtering filter taps including pixels of the far-infrared image, the near-infrared image, and the visible light image.

Abstract: The present disclosure relates to an image processing apparatus, an image processing method, and a program which can suppress degradation of image quality when power consumption of a display unit is reduced by reducing luminance of an image. A determining unit determines a reduction amount of luminance of a pixel based on characteristics of each pixel of an input image. A reducing unit reduces the luminance of the pixel of the input image by the reduction amount determined by the determining unit. The present disclosure can be applied to, for example, an image processing apparatus, or the like, which reduces luminance of a pixel based on characteristics of each pixel of an input image and displays the input image whose luminance is reduced.

Abstract: An image processor includes a first acquirer that acquires a matching tap having a target pixel at the center, a second acquirer that acquires plural matching taps each having, at the center, one of pixels in a search area including the pixels surrounding the target pixel, a similarity identifier that identifies, among the matching taps acquired by the second acquirer, a similarity maximizing pixel representing a central pixel of the matching tap having the highest similarity to the matching tap acquired by the first acquirer, and a mixing controller that computes a pixel value of the target pixel by mixing a pixel value obtained by performing a predetermined arithmetic process on pixel values of a prediction tap having the target pixel at the center with a pixel value obtained by performing a predetermined arithmetic process on pixel values of a prediction tap having the similarity maximizing pixel at the center.

Abstract: An image processing device includes a calculation unit which calculates a luminosity of an environmental light of an image for each region based on an overall average value which is an average value of the luminosity of all pixels forming the image of an object and region average values which are the average values of the luminosity of the pixels for each region that is obtained by dividing the image, and a generation unit which generates a virtual captured image which is an image of the object when the object is illuminated with light from a predetermined position based on the luminosity of the environmental light for each of the regions of the image that is calculated by the calculation unit and the image.

Abstract: There is provided an image processing device including a weight calculation unit that calculates a weight corresponding to each of a plurality of pixel values centering on a pixel of interest of an input image based on a feature amount calculated based on the plurality of pixel values centering on the pixel of interest, a regression coefficient reading unit that reads a regression coefficient stored for each class code determined based on a plurality of pixel values corresponding to the pixel of interest of the input image, and a pixel value calculation unit that calculates a pixel value of a pixel of interest of an output image by performing calculation using the plurality of pixel values, the weights, and the regression coefficients centering on the pixel of interest of the input image.

Abstract: An image processing apparatus includes: a noise reduction processing amount calculator configured to calculate a noise reduction processing amount based on input image data and previous-frame output image data subjected to data compression/decompression processing; a feedback ratio correction unit configured, based on compression error information, to output the uncorrected noise reduction processing amount calculated by the noise reduction processing amount calculator with regard to a pixel having a noise reduction feedback ratio less than 100%, and to correct the noise reduction processing amount with regard to a pixel having a noise reduction feedback ratio of 100% or more such that the feedback ratio is less than 100%, and to output the corrected noise reduction processing amount; and an adder configured to add the noise reduction processing amount output from the feedback ratio correction unit to the input image data to thereby obtain output image data.

Abstract: There is provided an image processing device including a weight calculation unit that calculates a weight corresponding to each of a plurality of pixel values centering on a pixel of interest of an input image based on a feature amount calculated based on the plurality of pixel values centering on the pixel of interest, a regression coefficient reading unit that reads a regression coefficient stored for each class code determined based on a plurality of pixel values corresponding to the pixel of interest of the input image, and a pixel value calculation unit that calculates a pixel value of a pixel of interest of an output image by performing calculation using the plurality of pixel values, the weights, and the regression coefficients centering on the pixel of interest of the input image.