# US 2014/0193069 A1 · Method and device for processing an image to remove color fringe > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0193069 A1 - Document ID: US20140193069A1 - Status: Published application - Kind: A1 - Application number: 13/739,492 - Filed: 2013-01-11 - Published: 2014-07-10 - Earliest claimed: 2013-01-10 - Assignees: Industry-University Cooperation Foundation Sogang University; Samsung Electronics Co., Ltd. - Applicants: Samsung Electronics Co., Ltd. - Inventors: TAE CHAN KIM; WON HO CHO; HAE JIN JU; RAE HONG PARK; DONG KYU LEE - Web page: https://patentgrep.com/patent/US20140193069A1 ## CPC - G06T 5/30: Erosion or dilatation, e.g. thinning - G06T 5/77: Retouching; Inpainting; Scratch removal - G06T 2207/10024: Color image - G06T 2207/20192: Edge enhancement; Edge preservation - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract In image processing, a color fringe is removed. The processing includes selecting a maximum gradient magnitude among gradient magnitudes for each of color components in an image, calculating a boundary of a dilated near-saturation region in the image, detecting a transition region in the image according to the maximum gradient magnitude and the dilated near-saturation region, and removing a color fringe from the transition region. ## Claims ### Claim 1 An image processing method, comprising: selecting a maximum gradient magnitude among gradient magnitudes for each of color components of an image; calculating a boundary of a dilated near-saturation region in the image; detecting a transition region in the image according to the maximum gradient magnitude and a boundary of the dilated near-saturation region; and removing a color fringe from the transition region to obtain a processed image. ### Claim 2 (depends on 1) The method of claim 1, wherein each of gradient magnitudes for each of the color components represents a greatest value among gradient magnitudes, calculated by using each of vertical, horizontal, diagonal and anti-diagonal sobel masks, for each of the color components. ### Claim 3 (depends on 1) The method of claim 1, further comprising selecting a direction label for at least one of the color components at an arbitrary point of the image, wherein the direction label is used to detect the transition region. ### Claim 4 (depends on 3) The method of claim 3, wherein the direction label is one of v, h, d and ad, and wherein v represents vertical, h represents horizontal, d represents diagonal, and ad represents anti-diagonal. ### Claim 5 (depends on 1) The method of claim 1, wherein a boundary value of the dilated near-saturation region in the detected transition region is 1. ### Claim 6 (depends on 1) The method of claim 1, wherein the maximum gradient magnitude is greater than a threshold value in the detected transition region. ### Claim 7 (depends on 3) The method of claim 3, wherein, when each of direction labels is selected for each of the color components, at least two of the direction labels for each of the color components are the same in the detected transition region. ### Claim 8 (depends on 1) The method of claim 1, wherein calculating a boundary of a dilated near-saturation region in the image includes: calculating a near-saturation region by comparing a luma component value with a threshold value in the image; calculating a dilated near-saturation region by using the near-saturation region and a dilation operation of a structuring element; and calculating a boundary of the dilated near-saturation region using difference between the near-saturation region and the dilated near-saturation region. ### Claim 9 (depends on 1) The method of claim 1, wherein removing a color fringe in the transition region includes: calculating leftmost pixel coordinates and rightmost pixel coordinates in the transition region according to the maximum gradient magnitude; and removing a color fringe from the transition region by using a maximum value and a minimum value of a color difference at the leftmost pixel coordinates and the rightmost pixel coordinates. ### Claim 10 (depends on 1) The method of claim 1, wherein removing a color fringe from the transition region includes: calculating a degree of color fringe occurrence for each color fringe in the transition region; determining a greatest value among the degrees of the color fringe occurrence as a color degree; calculating a saturation value by using values of chroma components in the image; calculating weight values of each pixel in the transition region by using the color degree and the saturation value; and correcting the chroma components by using the weight values of each pixel. ### Claim 11 An image processing method, comprising: receiving a digital image signal including color components for each of plural pixels constituting an image frame; selecting a maximum gradient magnitude among gradient magnitudes for each of the color components of the image frame; calculating a boundary of a dilated near-saturation region in the image frame; detecting a transition region in the image frame according to the maximum gradient magnitude and a boundary of the dilated near-saturation region; generating a processed digital image signal in which a color fringe from the transition region has been removed. ### Claim 12 (depends on 11) The method of claim 11, wherein each of gradient magnitudes for each of the color components represents a greatest value among gradient magnitudes, calculated by using each of vertical, horizontal, diagonal and anti-diagonal sobel masks, for each of the color components. ### Claim 13 (depends on 11) The method of claim 11, further comprising selecting a direction label for at least one of the color components at an arbitrary point of the image, wherein the direction label is used to detect the transition region. ### Claim 14 (depends on 13) The method of claim 13, wherein the direction label is one of v, h, d and ad, and wherein v represents vertical, h represents horizontal, d represents diagonal, and ad represents anti-diagonal. ### Claim 15 An image processor, comprising: a gradient magnitude unit for selecting a maximum gradient magnitude among gradient magnitudes for each of color components in an image; a near-saturation region detection unit for calculating a boundary of a dilated near-saturation region in the image; a transition region detection unit for detecting a transition region in the image according to the maximum gradient magnitude and a boundary of the dilated near-saturation region; and a correction block for removing a color fringe from the transition region. ### Claim 16 (depends on 15) The image processor of claim 15, further comprising a gradient direction label unit for selecting a direction label for at least one of the color components at an arbitrary point in the image. ### Claim 17 (depends on 15) The image processor of claim 15, wherein the correction block calculates leftmost pixel coordinates and rightmost pixel coordinates of the transition region according to the maximum gradient magnitude, and removes a color fringe from the transition region by using a maximum value and a minimum value of a color difference at the leftmost pixel coordinates and the rightmost pixel coordinates. ### Claim 18 (depends on 15) The image processor of claim 15, wherein the correction block calculates a degree of color fringe occurrence for each color fringe in the transition region, determines a greatest value among the degrees of color fringe occurrence as a color degree, calculates a saturation value by using values of chroma components in the image, calculates weight values of each pixel in the transition region by using the color degree and the saturation value, and corrects the chroma components by using the weight values of each pixel. ### Claim 19 (depends on 15) A system comprising the image processor of claim 15, a host processor, a memory and interface communicating over a bus system. ### Claim 20 (depends on 19) The system of claim 19, wherein the system is embodied as at least one of a mobile phone, a smart phone, a tablet PC, a personal digital assistant (PDA), an enterprise digital assistant (EDA), a digital still camera, a digital video camera, a portable multimedia player (PMP), a personal navigation device or portable navigation device (PDN), a smart TV, handheld game console, a security camera, and an e-book.