Abstract: A method and an image processing device for adjusting a stereo image are provided. The method includes: obtaining a disparity map between a first image and a second image; dividing the disparity map into layers which correspond to first layers of the first image and second layers of the second image; generating a first cost according to displacements of pixels of an ith first layer and an ith second layer; generating a second cost according to a difference between displacements of pixels of the ith first layer and a jth first layer, and a difference between displacements of pixels of the ith second layer and a jth second layer; executing an optimization algorithm at least according to the first cost and the second cost to obtain all the displacements; and adjusting the positions of the corresponding pixels according to the displacements. Therefore, a viewer may have a better viewing experience.

Abstract: An image processing method for image alignment, includes sequentially receiving a plurality of images; generating at least one threshold corresponding to each image according to a plurality of intensities of each image of the plurality of images; converting each image according to the thresholds of each image, for generating a plurality of binary images; acquiring a plurality of characteristic pixels of each binary image according to the plurality of binary images; and aligning the plurality of images according to the plurality of characteristic pixels of each binary image.

Abstract: A method for correcting a rolling shutter effect is provided. The method includes: obtaining feature point pairs in images, wherein each of the feature point pairs corresponds to a motion vector; obtaining sampling points between two consecutive images in time; setting a moving velocity and an angular velocity of an image capturing unit at each of the sampling points as variables; obtaining estimating motion vectors according to the variables, a focal length of the image capturing unit, and row locations where the feature point pairs are located; executing an optimization algorithm according to a difference between the motion vectors and the estimating motion vectors, to calculate the moving velocity and the angular velocity corresponding to the variables; varying locations of pixels in an image according to the moving velocity and the angular velocity, to generate a first corrected image. Thereby, the rolling shutter effect in an image is removed.

Abstract: An image processing method for image alignment, includes sequentially receiving a plurality of images; generating at least one threshold corresponding to each image according to a plurality of intensities of each image of the plurality of images; converting each image according to the thresholds of each image, for generating a plurality of binary images; acquiring a plurality of characteristic pixels of each binary image according to the plurality of binary images; and aligning the plurality of images according to the plurality of characteristic pixels of each binary image.

Abstract: A method and an image processing device for adjusting a stereo image are provided. The method includes: obtaining a disparity map between a first image and a second image; dividing the disparity map into layers which correspond to first layers of the first image and second layers of the second image; generating a first cost according to displacements of pixels of an ith first layer and an ith second layer; generating a second cost according to a difference between displacements of pixels of the ith first layer and a jth first layer, and a difference between displacements of pixels of the ith second layer and a jth second layer; executing an optimization algorithm at least according to the first cost and the second cost to obtain all the displacements; and adjusting the positions of the corresponding pixels according to the displacements. Therefore, a viewer may have a better viewing experience.

Abstract: A method for correcting a rolling shutter effect is provided. The method includes: obtaining feature point pairs in images, wherein each of the feature point pairs corresponds to a motion vector; obtaining sampling points between two consecutive images in time; setting a moving velocity and an angular velocity of an image capturing unit at each of the sampling points as variables; obtaining estimating motion vectors according to the variables, a focal length of the image capturing unit, and row locations where the feature point pairs are located; executing an optimization algorithm according to a difference between the motion vectors and the estimating motion vectors, to calculate the moving velocity and the angular velocity corresponding to the variables; varying locations of pixels in an image according to the moving velocity and the angular velocity, to generate a first corrected image. Thereby, the rolling shutter effect in an image is removed.

Abstract: A signal correcting method and a circuit thereof are provided. In the method, first, the values of a plurality of input signals are clamped to generate a plurality of corresponding clamping signals according to a plurality of adjustable predetermined values. Then, a combined multiplication operation is performed to the clamping signals according to the coefficients in a matrix obtained by multiplying the coefficients in at least two predetermined correcting matrixes, so as to output a plurality of results. Next, the results are respectively clamped according to a plurality of corresponding predetermined thresholds so as to output the corrected input signals.

Abstract: A face detection apparatus and a face detection method thereof are provided. The face detection apparatus includes a rectangle integral image unit, a feature mapping unit and a cascade and score unit. The rectangle integral image unit provides a rectangle integral image according to an original image. The feature mapping unit determines a face candidate region according to rectangular face feature templates, and calculates feature values of the rectangular face feature templates according to the rectangle integral image. The cascade and score unit judges whether the face candidate region conforms to cascade conditions or not, and gives the face candidate region a score according to the feature values when the face candidate region conforms to the cascade conditions. The face candidate region is a non-face region if the score of the face candidate region is lower than a threshold value.

Abstract: An image noise reduction method is provided. An image is received. A first-stage process is performed to the image to obtain a luminance information Y and a color information Cb and/or Cr corresponding to a pixel array in an YCbCr domain. A second-stage process is performed to the luminance information Y to reduce at least a luminance noise. A third-stage process is performed to the color information Cb and/or Cr to reduce at least a color noise. The luminance information Y and the color information Cb and/or Cr are then combined.

Abstract: A pixel unit in the present invention is divided into two sub-pixels. Each sub-pixel includes a thin film transistor, a liquid crystal capacitor and a storage capacitor. The two transistors respectively located in different sub-pixels are connected to different scan lines. One of the two transistors is connected to the data line through another transistor. Therefore, two different pixel voltages are formed in a pixel.

Abstract: A focusing method, suitable for an image capturing apparatus using in an environment of low brightness, is provided herein. The focusing method includes that an image sensing unit in the image capturing apparatus is wholly or partially divided into a plurality of regions, and digital image data sensed by the image sensing unit is divided into a plurality of sets corresponding to the regions of the image sensing unit. The regional image data corresponding to each of the regions are summed up during the focusing step, so as to obtain a sum of data for each region. Each sum of data is used to calculate a corresponding contrast value, and the contrast value is used to perform calculations for the focusing step, so as to obtain a focus.

Abstract: A pixel unit in the present invention is divided into two sub-pixels. Each sub-pixel includes a thin film transistor, a liquid crystal capacitor and a storage capacitor. The two transistors respectively located in different sub-pixels are connected to different scan lines. One of the two transistors is connected to the data line through another transistor. Therefore, two different pixel voltages are formed in a pixel.

Abstract: A face detection apparatus and a face detection method thereof are provided. The face detection apparatus includes a rectangle integral image unit, a feature mapping unit and a cascade and score unit. The rectangle integral image unit provides a rectangle integral image according to an original image. The feature mapping unit determines a face candidate region according to rectangular face feature templates, and calculates feature values of the rectangular face feature templates according to the rectangle integral image. The cascade and score unit judges whether the face candidate region conforms to cascade conditions or not, and gives the face candidate region a score according to the feature values when the face candidate region conforms to the cascade conditions. The face candidate region is a non-face region if the score of the face candidate region is lower than a threshold value.

Abstract: An image noise reduction method is provided. An image is received. A first-stage process is performed to the image to obtain a luminance information Y and a color information Cb and/or Cr corresponding to a pixel array in an YCbCr domain. A second-stage process is performed to the luminance information Y to reduce at least a luminance noise. A third-stage process is performed to the color information Cb and/or Cr to reduce at least a color noise. The luminance information Y and the color information Cb and/or Cr are then combined.

Abstract: A determination method for white-point and a correction method of the white balance are disclosed. In the determination method for white-point of the white balance, first gray cards with different reflection coefficients are detected according to the properties of an image sensing device. Next, the white-point gray line of a first color temperature and the white-point gray line of a second color temperature are intersected on a white-point plane to form a fan area, so as to set the white-point range of the low saturation of the image sensing device. Next, the vertical projection for an image datum is calculated to obtain a placement datum on the white-point plane, and a difference value between the image datum and the placement datum is calculated. Finally, whether the image datum is a white-point is determined according to the difference value and relationship between the placement datum and the fan area.

Abstract: A signal correcting method and a circuit thereof are provided. In the method, first, the values of a plurality of input signals are clamped to generate a plurality of corresponding clamping signals according to a plurality of adjustable predetermined values. Then, a combined multiplication operation is performed to the clamping signals according to the coefficients in a matrix obtained by multiplying the coefficients in at least two predetermined correcting matrixes, so as to output a plurality of results. Next, the results are respectively clamped according to a plurality of corresponding predetermined thresholds so as to output the corrected input signals.

Abstract: A focusing method, suitable for an image capturing apparatus using in an environment of low brightness, is provided herein. The focusing method includes that an image sensing unit in the image capturing apparatus is wholly or partially divided into a plurality of regions, and digital image data sensed by the image sensing unit is divided into a plurality of sets corresponding to the regions of the image sensing unit. The regional image data corresponding to each of the regions are summed up during the focusing step, so as to obtain a sum of data for each region. Each sum of data is used to calculate a corresponding contrast value, and the contrast value is used to perform calculations for the focusing step, so as to obtain a focus.