Abstract: The present invention discloses a video processing method and apparatus, and an electronic device. The video processing method includes: controlling N camera units in one electronic device to simultaneously acquire N paths of video data, wherein the N camera units are simultaneously turned on under a control of a same control unit in the electronic device, and N is an integer not less than 2; obtaining a processing result by processing a plurality of paths of video data in the N paths of video data; and displaying the processing result on a display screen of the electronic device. By means of the present invention, it is possible to solve the technical problem in the related art that a plurality of cameras are usually turned on at different times respectively in a camera switching mode, such that data collected by the plurality of cameras cannot be acquired at the same time.

Abstract: A method for merging first and second images includes determining a pixel difference image from the first and the second images, determining first and second locations of the foreground subject from the pixel difference image, determining a minimum path of values from the pixel difference image for a region between the first and the second locations of the foreground subject, forming a merged image by stitching the first and the second images along the minimum path, and adjusting pixels of the merged image within a width of the minimum path.

Abstract: A method of automatic photographs stitching in a photograph capturing electronic apparatus by capturing a photograph; on a viewfinder or display screen of said photograph capturing electronic apparatus, displaying at least one four-way guiding arrow for advising user the direction to move the photograph capturing electronic apparatus for capturing the next photograph which is suitable for stitching, the next suitable photograph having at a predetermined region, an area overlapped and aligned to the captured photograph with the overlapped and aligned area reaching a predetermined proportion; capturing the next suitable photograph; and stitching the consecutively captured photographs into a panoramic photograph.

Abstract: A method for color matching a first image and a second image, wherein a first region of the first image and a second region of the second image overlap, includes removing overlapping pixels in the first and the second regions that have pixel values are too different, generating a first histogram of the first region, generating a second histogram of the second region, determining corresponding pixel values in the first and the second histograms, determining parameters of an optoelectronic conversion function that matches the corresponding pixel values, and color matching the second image to the first image by applying the optoelectronic conversion function with the determined parameters to the second image.

Abstract: A method is provided for processing minimum coded units (MCUs) in a Joint Photographic Expert Group (JPEG) bit stream representing an image. A data structure is generated for storing MCU block numbers, corresponding MCU block coordinates, and corresponding MCU block editing lists. When an editing operation to the image is received, the editing operation is saved to a group of the MCU block editing lists of a group of the MCUs affected by the editing operation. Later the MCUs are retrieved from the JPEG bit stream one at a time and then processed according to the editing operations in the corresponding MCU blocking editing lists.

Abstract: A method of automatic photographs stitching in a photograph capturing electronic apparatus, said method comprising the steps of capturing a photograph; on a viewfinder or display screen of said photograph capturing electronic apparatus, displaying at least one four-way guiding arrow for advising user the direction to move said photograph capturing electronic apparatus for capturing the next photograph which is suitable for stitching, said next suitable photograph having at a predetermined region, an area overlapped and aligned to said captured photograph with said overlapped and aligned area reaching a predetermined proportion; capturing the next suitable photograph; and stitching said consecutively captured photographs into a panoramic photograph.

Abstract: A method for merging first and second images includes determining a pixel difference image from the first and the second images, determining first and second locations of the foreground subject from the pixel difference image, determining a minimum path of values from the pixel difference image for a region between the first and the second locations of the foreground subject, forming a merged image by stitching the first and the second images along the minimum path, and adjusting pixels of the merged image within a width of the minimum path.

Abstract: A method is provided for processing minimum coded units (MCUs) in a Joint Photographic Expert Group (JPEG) bit stream representing an image. A data structure is generated for storing MCU block numbers, corresponding MCU block coordinates, and corresponding MCU block editing lists. When an editing operation to the image is received, the editing operation is saved to a group of the MCU block editing lists of a group of the MCUs affected by the editing operation. Later the MCUs are retrieved from the JPEG bit stream one at a time and then processed according to the editing operations in the corresponding MCU blocking editing lists.

Abstract: A method for generating a panoramic image includes receiving a first image, dividing the first image into a first portion and a second portion, rotating the first portion of the first image, saving the rotated first portion of the first image in a nonvolatile memory, receiving a second image, dividing the second image into a third portion and a fourth portion, matching an overlapping region between the second portion of the first image and the third portion of the second image, stitching the second portion of the first image and the third portion of the second image to form a first stitched image, rotating the first stitched image, and saving the first stitched image in the nonvolatile memory.

Abstract: A method for removing red eyes includes (1) identifying potential red eye pixels in a low resolution image (hereafter “LR red eye pixels”), (2) grouping contiguous LR red eye pixels into red eye regions (herafter “LR red eye regions”), (3) determining working areas around the LR red eye regions (hereafter “LR working areas”), (4) determining classifiers from the LR working areas, (5) retrieving working areas from a high resolution image that correspond to the LR working areas (hereafter “HR working areas”), (6) applying the classifiers to the HR working areas to identify potential red eye pixels (hereafter “HR red eye pixels”), (7) grouping contiguous HR red eye pixels into red eye regions (hereafter “HR red eye regions”), (8) determining some of the HR red eye regions as the red eyes, and (9) replacing the HR red eye pixels in the red eyes with black pixels.

Abstract: A method for creating a 360 degree panoramic image from multiple images includes (1) computing a gross rotation error ?R between a first image and a calculated first image rotated to be stitched to a last image, and (2) spreading the gross rotation error ?R to each pixel on the panoramic image. Spreading the gross rotation error ?R includes (1) computing a rotation angle ?0 and rotational axis n0 from the gross rotational error ?R, (2) determining an angle ? of each pixel, and (3) determining a compensation matrix Rc for each pixel using the following formula: Rc(?)=R(?/2??0).

Abstract: A method for indexing minimum coded units (MCUs) in a Joint Photographic Expert Group (JPEG) bit stream includes (1) entropy decoding a first MCU to determine a bit offset of a second MCU and a DC coefficient of the first MCU, wherein the first MCU immediately precedes the second MCU in the bit stream, and (2) indexing the second MCU by storing the bit offset and the DC coefficient in an index. The method may further include (3) receiving a request for the second MCU, (4) reading the index to determine the bit offset of the second MCU and the DC coefficient of the first MCU, and (5) entropy decoding the second MCU starting at its bit offset in the bit stream, wherein the entropy decoding the second MCU includes determining a DC coefficient of the second MCU using the DC coefficient of the first MCU.

Abstract: A method for aligning images includes (1) selecting a pair of overlapping pixels when two second image are aligned with a camera motion; (2) if both pixels are edge pixels, incrementing a correlation value between the two images for the camera motion; (3) if only one of pixels is an edge pixel, decrementing the correlation value between the two images for the camera motion; (4) repeating steps (1) to (3) for other pairs of overlapping pixels in the two images to determine the correlation value for the camera motion. The method further includes (5) repeating steps (1) to (4) for other camera motions; (6) selecting camera motions having large correlation values; (7) determining matched edge counts for members of the group; (8) selecting the camera motion with the largest matched edge count; and (8) aligning the two images with the selected camera motion.

Abstract: A method for removing red eyes includes (1) identifying potential red eye pixels in a low resolution image (hereafter “LR red eye pixels”), (2) grouping contiguous LR red eye pixels into red eye regions (herafter “LR red eye regions”); determining working areas around the LR red eye regions (hereafter “LR working areas”), (3) determining classifiers from the LR working areas, (4) retrieving working areas from a high resolution image that correspond to the LR working areas (hereafter “HR working areas”), (5) applying the classifiers to the HR working areas to identify potential red eye pixels (hereafter “HR red eye pixels”), (6) grouping contiguous HR red eye pixels into red eye regions (hereafter “HR red eye regions”), (7) determining some of the HR red eye regions as the red eyes, and (8) replacing the HR red eye pixels in the red eyes with black pixels.

Abstract: A method includes (1) generating a first image pyramid of a first image, (2) generating a second image pyramid of a second image, (3) warping a first level image of the first image pyramid with a motion field, (4) determining a residual motion field from the warped first level image of the first image pyramid and a corresponding first level image of the second image pyramid, and (5) if the residual motion field is not less than a threshold, adding the residual motion field to the motion field and repeating steps (3) and (4).

Abstract: A method for generating a panoramic image includes receiving a first image, dividing the first image into a first portion and a second portion, rotating the first portion of the first image, saving the rotated first portion of the first image in a nonvolatile memory, receiving a second image, dividing the second image into a third portion and a fourth portion, matching an overlapping region between the second portion of the first image and the third portion of the second image, stitching the second portion of the first image and the third portion of the second image to form a first stitched image, rotating the first stitched image, and saving the first stitched image in the nonvolatile memory.

Abstract: A method for color matching a first image and a second image, wherein a first region of the first image and a second region of the second image overlap, includes removing overlapping pixels in the first and the second regions that have pixel values are too different, generating a first histogram of the first region, generating a second histogram of the second region, determining corresponding pixel values in the first and the second histograms, determining parameters of an optoelectronic conversion function that matches the corresponding pixel values, and color matching the second image to the first image by applying the optoelectronic conversion function with the determined parameters to the second image.

Abstract: A method for aligning images includes (1) selecting a pair of overlapping pixels when two second image are aligned with a camera motion; (2) if both pixels are edge pixels, incrementing a correlation value between the two images for the camera motion; (3) if only one of pixels is an edge pixel, decrementing the correlation value between the two images for the camera motion; (4) repeating steps (1) to (3) for other pairs of overlapping pixels in the two images to determine the correlation value for the camera motion. The method further includes (5) repeating steps (1) to (4) for other camera motions; (6) selecting camera motions having large correlation values; (7) determining matched edge counts for members of the group; (8) selecting the camera motion with the largest matched edge count; and (8) aligning the two images with the selected camera motion.

Abstract: A method for indexing minimum coded units (MCUs) in a Joint Photographic Expert Group (JPEG) bit stream includes (1) entropy decoding a first MCU to determine a bit offset of a second MCU and a DC coefficient of the first MCU, wherein the first MCU immediately precedes the second MCU in the bit stream, and (2) indexing the second MCU by storing the bit offset and the DC coefficient in an index. The method may further include (3) receiving a request for the second MCU, (4) reading the index to determine the bit offset of the second MCU and the DC coefficient of the first MCU, and (5) entropy decoding the second MCU starting at its bit offset in the bit stream, wherein the entropy decoding the second MCU includes determining a DC coefficient of the second MCU using the DC coefficient of the first MCU.

Abstract: A method for creating a 360 degree panoramic image from multiple images includes (1) computing a gross rotation error &Dgr;R between a first image and a calculated first image rotated to be stitched to a last image, and (2) spreading the gross rotation error &Dgr;R to each pixel on the panoramic image. Spreading the gross rotation error &Dgr;R includes (1) computing a rotation angle &thgr;0 and rotational axis n0 from the gross rotational error &Dgr;R, (2) determining an angle &agr; of each pixel, and (3) determining a compensation matrix Rc for each pixel using the following formula: R,(a)=R(2&pgr;/&agr;&thgr;0).