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 a method that perform a false color correction according to image characteristics of a color image in units of image regions are provided. Included therein is an image processor that receives inputs of a color image and a white (W) image photographed by a W array imaging element whose all pixels are placed in a white (W) pixel array and executes an image process that reduces false colors included in the color image. Together with a frequency-corresponding parameter calculation unit that receives an input of the white (W) image and calculates a frequency-corresponding parameter in units of image regions, and a positional deviation-corresponding parameter calculation unit that receives inputs of the white (W) image and the color image and calculates a positional deviation-corresponding parameter of the two input images in units of image regions, the image processor executes a blending process and calculates a corrected pixel value.
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. Alternatively, the transmittance detection unit converts a grayscale of the transmittance estimated for each of the regions from the captured image into a grayscale of the depth indicated by the depth information for each of the regions and sets the transmittance after the grayscale conversion as the transmission of the haze. This enables the transmittance to be detected with high accuracy.
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:
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.