Abstract: A method of image processing includes: providing a radiance map, generating a first image in which an edge part is preserved and a flat part is smoothed by applying an edge preservation smoothing filter to the radiance map, generating a second image having a visually perceivable dynamic range by applying a correction curve to the first image, and generating a display image having corrected lightness by adjusting a hue value and a chroma value of the second image.

Abstract: An image processing method and apparatus for obtaining a wide dynamic range image, the method including: obtaining a plurality of low dynamic range images having different exposure levels for a same scene; generating motion map representing whether motion occurred, depending on brightness ranks of the plurality of low dynamic range images; obtaining weights for the plurality of low dynamic range images; generating a weight map by combining the weights and the motion map; and generating a wide dynamic range image by fusing the plurality of low dynamic range images and the weight map. According to the image processing method and apparatus, it is possible to accurately detect motion area using a rank map, obtain a wide dynamic range image at a higher operation speed, and reduce a possibility that a phenomenon such as color warping occurs by directly combining images without using a tone mapping process.

Abstract: An image processing method and image processing apparatus for removing noise from an image. The image processing method includes: dividing an input image into a high frequency component and a low frequency component; removing noise from the high frequency component; and combining the low frequency component and the high frequency component from which noise is removed to form an output image. Accordingly, an image in which edge components are well preserved and a degree of color noise is reduced may be generated not only in a general environment but also in a low light level and highly sensitive environment having strong noise.

Abstract: An image processing method and an image processing apparatus for removing noise from an image are disclosed. A provided image processing method includes: dividing an input image into a luminance signal and a chrominance signal; removing noise from the luminance signal; restoring luminance signal present in the noise removed from the luminance signal; removing noise from the chrominance signal; and combining the luminance signal and the chrominance signal from which the noises are removed. Accordingly, an image of which an edge component is well preserved and a degree of color noise is low is generated not only in a general environment but also in a low light level and high sensitivity environment having a large amount of noise.

Abstract: A digital photographing apparatus capable of acquiring data about an image having a wide dynamic range and a high grayscale resolution, a method of controlling the digital photographing apparatus, and a recording medium storing a program to implement the method are provided. An embodiment includes an imaging device that acquires a reference image and additional images at different exposures and a multi-level threshold map generation unit that classifies the pixels of the images into levels according to brightness. The embodiment further includes a motion data acquiring unit that acquires motion data for each pixel based on its respective brightness level and a first weight data acquiring unit that acquires first weight data based on the motion data of each pixel. In addition, the embodiment includes a final image data acquiring unit that synthesizes the pixels of the reference image and the additional images based on first weight data.

Abstract: Provided is a method for assessing image quality using quantization codes, which includes: filtering an original image and a distorted image; generating phase quantization codes from the filtering result; calculating a Hamming difference between the phase quantization code of the original image and the phase quantization code of the distorted image; and assessing image quality of the distorted image by using the calculated Hamming difference. According to the present disclosure, since pixel values of the original image and the distorted image are mapped onto a quantized complex plane and then binary code operation is performed, it is possible to easily implement to image quality assessing hardware and also ensure excellent image quality assessing performance.

Abstract: Provided are an image processing method and apparatus for enhancing contrast. The image processing apparatus includes a determination unit that determines whether contrast enhancement processing should be performed on an input image; an intensity mapping unit that generates a plurality of images having different exposure times from the input image, using intensity mapping, if the contrast enhancement processing should be performed on the input image; and an image composition unit that composes the plurality of images into a composed image. Therefore, it is possible to reduce a color change or a false contour phenomenon that are generated in a related art contrast enhancement process.

Abstract: An image processing apparatus and an image processing method, the method including: providing one or more low dynamic range images having different exposure levels; classifying each of the one of more low dynamic range images as a saturation region, an under-saturation region, and a non-saturation region with respect to an intensity value; generating feature maps indicating a similarity between patterns of the non-saturation regions; generating final feature maps converting pixels included in the feature maps into moving pixels and non-moving pixels; defining moving regions and non-moving regions included in the one or more low dynamic range images; removing noise from the moving regions and the non-moving regions by using a first noise reduction filter for the moving regions and a second noise reduction filter for the non-moving regions; and generating a radiance map corresponding to the one or more low dynamic range images.

Abstract: A method of image processing includes: providing a radiance map, generating a first image in which an edge part is preserved and a flat part is smoothed by applying an edge preservation smoothing filter to the radiance map, generating a second image having a visually perceivable dynamic range by applying a correction curve to the first image, and generating a display image having corrected lightness by adjusting a hue value and a chroma value of the second image.

Abstract: A method of improving picture quality in a composite video burst signal includes dividing the composite video burst signal into a plurality of frequency bands using a low pass filter and a high pass filter, performing wavelet packet filtering of frequency bands including a chrominance signal having energy higher than a specified threshold among the plurality of frequency bands, and performing Wiener filtering of frequency bands including a chrominance signal having energy lower than a specified threshold.

Abstract: A digital photographing apparatus capable of acquiring data about an image having a wide dynamic range and a high grayscale resolution, a method of controlling the digital photographing apparatus, and a recording medium storing a program to implement the method are provided. An embodiment includes an imaging device that acquires a reference image and additional images at different exposures and a multi-level threshold map generation unit that classifies the pixels of the images into levels according to brightness. The embodiment further includes a motion data acquiring unit that acquires motion data for each pixel based on its respective brightness level and a first weight data acquiring unit that acquires first weight data based on the motion data of each pixel. In addition, the embodiment includes a final image data acquiring unit that synthesizes the pixels of the reference image and the additional images based on first weight data.

Abstract: An image interpolating method and apparatus, in which horizontal and vertical Differences of Absolute Inter-channel Differences (DAIDs) are calculated from a color filter array (CFA) image, and an unknown pixel is interpolated in horizontal and vertical directions estimated in consideration of the DAIDs of R, G, and B pixels. Therefore, the image interpolating method and apparatus provide a large Peak Signal and Noise Ratio (PSNR), a Structural Similarity (SSIM), and high visual quality images.

Abstract: A method for adaptive false contour reduction includes: detecting contour location information by removing a flat region having certain brightness values from a first input image based on a bright value difference between the first input image and a second input image with a bit depth of the first input image reduced; detecting false-contour direction and location information by measuring directional contrast of the flat region-removed first image, and distinguishing the false contour area and an edge area out of the false contour location information based on the measured contrast; and smoothing the false contour area by using the false contour direction and location information, and removing the false contour from the first input image. Thus, a flat region can be automatically removed by using a brightness value difference between a bit depth-reduced image and an original input image and detect a false contour, thereby enhancing a precision degree of false contour detection.

Abstract: A spatio-temporal noise removal method using block classification that removes noise from a third field by using first, second, and third fields which are continuously inputted. The method includes generating first, second, and third motion-compensated fields; classifying blocks of the third field into a uniform region and a non-uniform region based on a variance value of a generated difference image; performing temporal filtering over every block of the third field; performing spatio-temporal filtering over every block of the first and third motion-compensated fields and the third field and performing the temporal filtering over the every block of the third field based on spatially-filtered value; and outputting a third noise-removed field by applying a weighted value to the temporal-filtered value and the spatio-temporal-filtered value.

Abstract: An image resolution conversion method and apparatus based on a projection onto convex sets (POCS) method are provided. The image resolution conversion method comprises detecting an edge region and a direction of the edge region in an input low-resolution image frame in order to generate an edge map and edge direction information, generating a directional point spread function based on the edge map and the edge direction information, interpolating the input low-resolution image frame into a high-resolution image frame, generating a residual term based on the input low-resolution image frame, the high-resolution image frame, and the directional point spread function, and renewing the high-resolution image frame according to a result of comparing the residual term with a threshold.

Abstract: Provided are an image processing method and apparatus for enhancing contrast. The image processing apparatus includes a determination unit that determines whether contrast enhancement processing should be performed on an input image; an intensity mapping unit that generates a plurality of images having different exposure times from the input image, using intensity mapping, if the contrast enhancement processing should be performed on the input image; and an image composition unit that composes the plurality of images into a composed image. Therefore, it is possible to reduce a color change or a false contour phenomenon that are generated in a related art contrast enhancement process.

Abstract: A method of improving picture quality in a composite video burst signal includes dividing the composite video burst signal into a plurality of frequency bands using a low pass filter and a high pass filter, performing wavelet packet filtering of frequency bands including a chrominance signal having energy higher than a specified threshold among the plurality of frequency bands, and performing Wiener filtering of frequency bands including a chrominance signal having energy lower than a specified threshold.

Abstract: A method and apparatus for removing false contours while preserving edges. In the method, a false contour area is detected from an input image, false contour direction information and false contour location information of the false contour area are generated, the false contour area is expanded, and a false contour is removed from the expanded false contour area.

Abstract: A spatio-temporal noise removal method using block classification that removes noise from a third field by using first, second, and third fields which are continuously inputted. The method includes generating first, second, and third motion-compensated fields; classifying blocks of the third field into a uniform region and a non-uniform region based on a variance value of a generated difference image; performing temporal filtering over every block of the third field; performing spatio-temporal filtering over every block of the first and third motion-compensated fields and the third field and performing the temporal filtering over the every block of the third field based on spatially-filtered value; and outputting a third noise-removed field by applying a weighted value to the temporal-filtered value and the spatio-temporal-filtered value.

Abstract: A method for adaptive false contour reduction includes: detecting contour location information by removing a flat region having certain brightness values from a first input image based on a bright value difference between the first input image and a second input image with a bit depth of the first input image reduced; detecting false-contour direction and location information by measuring directional contrast of the flat region-removed first image, and distinguishing the false contour area and an edge area out of the false contour location information based on the measured contrast; and smoothing the false contour area by using the false contour direction and location information, and removing the false contour from the first input image. Thus, a flat region can be automatically removed by using a brightness value difference between a bit depth-reduced image and an original input image and detect a false contour, thereby enhancing a precision degree of false contour detection.