Abstract: A method and apparatus of auto focusing for a camera based on analysis of the image content in a target window are disclosed. According to the present invention, image content in a target window is analyzed to determine a state, a state change or both associated with the target window. The information associated with the state, the state change or both is provided to update the camera parameters. The state may be size, position, pose, behavior or gesture of one or more objects, or areas associated with one or more regions in the target window. The state may correspond to the motion field or optical flow associated with the target window. The state may correspond to object motion, extracted features or scales of the objects in the target window. The state may correspond to image content description of the segmented regions or deformable object contour in the target window.

Abstract: A noise elimination method of an image sequence is described. During a color separation of a raw image data captured by an image capturing element, 3D filtering is integrated. First, the raw image data is converted into a gray-scaled full luma image, an interframe filtering process is performed to eliminate possible noises in the gray-scaled full luma image, and an interpolation process is performed with the raw image data. During the implementation, an adaptive frame average filtering process is also performed to obtain a preferred image filtering result through an appropriate filtering manner. Therefore, an adaptive interframe interpolation for eliminating noises is to prevent noises or artifacts generated by the noises from affecting the subsequent image processing.

Abstract: An embodiment of the invention provides a method performed by an electronic device. According to the method, the electronic device first receives a shutter instruction. Then, in response to the shutter instruction, the electronic device automatically captures a plurality of images of a scene using a plurality of different focal distances, respectively.

Abstract: An image processing method includes: receiving a plurality of input images; deriving an image alignment related information from performing an image alignment upon the input images; and generating a processed image by performing a defocus operation upon a selected image selected from the input images according to the image alignment related information. For example, the image processing method may be employed by an electronic device such as a mobile device. Thus, the mobile device may capture two or more images to generate the defocus visual effect, which is similar to professional long-focus lens.

Abstract: A compression method is used for processing an image having a plurality of pixels, in which an image width of the image is W. The compression method includes the steps of selecting N continuous pixels from the image, where N is a positive integer greater than or equal to 2 and is less than the image width W; performing differential pulse code modulation (DPCM) so as to obtain N non-negative differences corresponding to the N pixels according to values of the N pixels; calculating to obtain a coding parameter according to the N non-negative differences; and coding the N non-negative differences according to the coding parameter.

Abstract: An image compression method s used for processing a plurality of pixels of an image. The image compression method includes the steps of receiving N successive pixels; obtaining N pixel differences and N map differences corresponding to the N pixels according to values of the N pixels through differential pulse code modulation; calculating to obtain a quantization reference value corresponding to the N pixels according to the N pixel differences; obtaining a quantization parameter corresponding to the N pixels according to the quantization reference value; and encoding the N map differences according to the quantization parameter.

Abstract: An integer division circuit with allowable error is described, what a signal processing apparatus includes a pointer, a first left shifter, a second left shifter, a subtractor, a multiplier, and a right shifter. The pointer searches for a most significant non-zero bit of a divisor and outputs a most significant byte value. The first left shifter performs a shift operation according to the most significant byte value, so as to generate a first exponential coefficient. The second left shifter performs a shift operation according to the most significant byte value, so as to generate a second exponential coefficient. The subtractor calculates a multiplier factor according to the divisor, the first exponential coefficient, and the second exponential coefficient and outputs the multiplier factor to the multiplier. The multiplier multiplies an input value with the multiplier factor and outputs a result to the right shifter. The right shifter outputs a calculation result.

Abstract: A method for beautifying a human face in a digital image is adapted to beautify a face area of an input image. The method includes setting a selection window to select a partial image area in the input image; setting a target pixel in the selection window, and setting other pixels as comparison pixels; performing a detail checking process according to a variance between the target pixel; performing a luminance checking process on the target pixel to determine; performing a nonlinear filtering process to filter the target pixel by using a nonlinear filter to generate a filtered value, and providing a mixing ratio to mix the target pixel with the filtered value at the mixing ratio to generate a completed pixel; replacing the original target pixel with the completed pixel; and repeating the above steps until all pixels are completed.

Abstract: A method of establishing a skin color model includes the following steps. A human face detecting procedure is performed on an input image, and a human face area in the input image is circled through a selecting window. A skin color model is established by using a Gaussian probability distribution function (PDF) according to color information in the selecting window. When the skin color model established in the above step is applied to skin color detection, pixels having the skin color in the input image are detected through the skin color model and a Mahalanobis distance computing procedure.

Abstract: An image compression method is used for processing a plurality of pixels of an image. The image compression method includes the steps of receiving N pixels; analyzing the N pixels and generating a content type corresponding to the N pixels; obtaining a quantization parameter and a coding parameter corresponding to the N pixels according to the content type and a currently available buffer space value; obtaining N quantized differences corresponding to the N pixels through a prediction and quantization way according to values of the N pixels and the quantization parameter; and encoding the N quantized differences according to the N quantized differences and the coding parameter.

Abstract: A method for adjusting a skin color of a digital image adjusts the skin color of an input image. The method includes performing a skin color detection process on the input image to generate a skin-color probability plot Sp in a size corresponding to the input image; providing a hue-saturation lookup table named LUT_Color; performing a skin-color reproduction process on the input image to look up the LUT_Color for a chrominance pixel value for each pixel value of the input image to generate a first image, and adjust each pixel value of the first image by using the skin-color probability plot Sp to generate a second image; performing a skin color smoothing process on the second image to generate a third image; and mixing pixel values of the input image and the third image to generate a target image.

Abstract: A color interpolation method for a digital image is described, includes the following steps. Edge information is generated according to the Bayer pattern. A Bayer pattern image is processed by a horizontal band-pass filter and a vertical band-pass filter to generate a horizontal edge signal and a vertical edge signal. A weight process implements a weight adjustment on the horizontal edge signal and the vertical edge signal to generate a luminance signal and outputs the luminance signal to a subtraction unit. The subtraction unit carries out an operation according to the Bayer pattern image and an output result of the weight process to generate a chrominance pattern. The chrominance pattern is compensated through a chrominance interpolation process, so as to generate image signal patterns of different colors. The image signal patterns of different colors are output to an adder for an add operation, thereby outputting a complete color image.

Abstract: An image compression method is used for processing a plurality of pixels of an image. The image compression method includes the steps of receiving N pixels; analyzing the N pixels and generating a content type corresponding to the N pixels; obtaining a quantization parameter and a coding parameter corresponding to the N pixels according to the content type and a currently available buffer space value; obtaining N quantized differences corresponding to the N pixels through a prediction and quantization way according to values of the N pixels and the quantization parameter; and encoding the N quantized differences according to the N quantized differences and the coding parameter.

Abstract: An image compression method s used for processing a plurality of pixels of an image. The image compression method includes the steps of receiving N successive pixels; obtaining N pixel differences and N map differences corresponding to the N pixels according to values of the N pixels through differential pulse code modulation; calculating to obtain a quantization reference value corresponding to the N pixels according to the N pixel differences; obtaining a quantization parameter corresponding to the N pixels according to the quantization reference value; and encoding the N map differences according to the quantization parameter.

Abstract: A compression method is used for processing an image having a plurality of pixels, in which an image width of the image is W. The compression method includes the steps of selecting N continuous pixels from the image, where N is a positive integer greater than or equal to 2 and is less than the image width W; performing differential pulse code modulation (DPCM) so as to obtain N non-negative differences corresponding to the N pixels according to values of the N pixels; calculating to obtain a coding parameter according to the N non-negative differences; and coding the N non-negative differences according to the coding parameter.

Abstract: An image noise reduction method based on an optimal primary-color signal is suitable for a digital camera to reduce noises in a digital image. The image noise reduction method mainly includes the following steps, taking out primary-color signals of a digital image, including taking out high-frequency and low-frequency signals of the optimal primary-color signal and high-frequency and low-frequency signals of the worst primary-color signal by using a high-pass filter and a low-pass filter; next, mixing the high-frequency signal of the optimal primary-color signal with that of the worst primary-color signal, and superposing the mixed signal to the low-frequency signal of the worst primary-color signal, so as to get a digital image signal after noise reduction.

Abstract: A color interpolation method for a digital image is described, includes the following steps. Edge information is generated according to the Bayer pattern. A Bayer pattern image is processed by a horizontal band-pass filter and a vertical band-pass filter to generate a horizontal edge signal and a vertical edge signal. A weight process implements a weight adjustment on the horizontal edge signal and the vertical edge signal to generate a luminance signal and outputs the luminance signal to a subtraction unit. The subtraction unit carries out an operation according to the Bayer pattern image and an output result of the weight process to generate a chrominance pattern. The chrominance pattern is compensated through a chrominance interpolation process, so as to generate image signal patterns of different colors. The image signal patterns of different colors are output to an adder for an add operation, thereby outputting a complete color image.

Abstract: A method for beautifying a human face in a digital image is adapted to beautify a face area of an input image. The method includes setting a selection window to select a partial image area in the input image; setting a target pixel in the selection window, and setting other pixels as comparison pixels; performing a detail checking process according to a variance between the target pixel; performing a luminance checking process on the target pixel to determine; performing a nonlinear filtering process to filter the target pixel by using a nonlinear filter to generate a filtered value, and providing a mixing ratio to mix the target pixel with the filtered value at the mixing ratio to generate a completed pixel; replacing the original target pixel with the completed pixel; and repeating the above steps until all pixels are completed.

Abstract: A method of establishing a skin color model includes the following steps. A human face detecting procedure is performed on an input image, and a human face area in the input image is circled through a selecting window. A skin color model is established by using a Gaussian probability distribution function (PDF) according to color information in the selecting window. When the skin color model established in the above step is applied to skin color detection, pixels having the skin color in the input image are detected through the skin color model and a Mahalanobis distance computing procedure.

Abstract: A noise elimination method of an image sequence is described. During a color separation of a raw image data captured by an image capturing element, 3D filtering is integrated. First, the raw image data is converted into a gray-scaled full luma image, an interframe filtering process is performed to eliminate possible noises in the gray-scaled full luma image, and an interpolation process is performed with the raw image data. During the implementation, an adaptive frame average filtering process is also performed to obtain a preferred image filtering result through an appropriate filtering manner. Therefore, an adaptive interframe interpolation for eliminating noises is to prevent noises or artifacts generated by the noises from affecting the subsequent image processing.