Abstract: An image de-noising method and an apparatus thereof are disclosed, which includes categorizing a pixel in a current frame into a first low-frequency pixel having a first weight and a first high-frequency pixel having a second weight; categorizing a previous pixel corresponding to the position of the pixel in a previous frame into a second low-frequency pixel having a third weight and a second high-frequency pixel having a fourth weight; adjusting the first weight and the third weight and calculating the weighted sum of the first low-frequency pixel and the second low-frequency pixel, to generate low-frequency pixel data; adjusting the second weight and the fourth weight and calculating the weighted sum of the first high-frequency pixel and the second high-frequency pixel, to generate high-frequency pixel data; and calculating the sum of the low-frequency pixel data and the high-frequency pixel data, to output the de-noised pixel.

Abstract: A fixed length code (FLC)-based image compression method and a device thereof. The method is utilized to compress a block containing plural pixels and includes the following steps: determining a first representative pixel, a second representative pixel and a third representative pixel from the pixels according to pixel values of the pixels, the three representative pixels being noncollinear in a color space to which the pixels correspond; generating plural first interpolated pixels by interpolation according to the first representative pixel and the third representative pixel; generating plural second interpolated pixels by interpolation according to the second representative pixel and the third representative pixel; and generating an index value for each pixel according to the three representative pixels, the first interpolated pixels and the second interpolated pixels.

Abstract: An image-filtering method that includes the steps outlined below is provided. Target image values and an input image having input pixel values are retrieved. A difference function between filtering response values of a desired output image and the target image values is determined, wherein the filtering response values are generated by filtering desired output pixel values of the desired output image based on characteristic filtering coefficients. An optimal solution of a desired output central pixel value of the desired output image is calculated according to a linear equation related to the characteristic filtering coefficients, wherein the optimal solution minimizes a value of the difference function. A corresponding relation between the desired output central pixel values and the input pixel values are retrieved from the optimal solution to calculate optimal filtering coefficients.

Abstract: A lifting device configured to adjustably hold a display device at a certain height includes a support frame configured to support the display device, a shaft, a toothed gear, and a rack secured on the support frame. The shaft includes a wide portion secured on the display device and a narrow portion carrying the toothed gear, friction between the wide portion and the narrow portion being sufficient to hold the static weight of the display device. The toothed gear meshes with the rack. An upward or downward push on the display device drives the gear to move up and down along the rack to adjust the height of the display device.

Abstract: A method for wide dynamic range imaging is illustrated. A region mapping operation having steps as follows is applied to an image using a plurality of region mapping curves for compensating different luminance associated with a plurality of regions in the image. A low frequency image is obtained. A reference value for each region in the image is obtained according to the low frequency image. One region mapping curve is selected according to the reference value of the region. A gain curve is obtained according to the selected region mapping curve, a gain value of a pixel value or a luminance value of the region is obtained according to the gain curve, an adjusted gain value is obtained according to the luminance corresponding to the pixel value, and the pixel value is adjusted according to the luminance value, the gain value, and the adjusted gain value.

Abstract: A method for generating a target gain value of a wide dynamic range (WDR) operation is disclosed including: acquiring an average bright portion luminance corresponding to an average pixel luminance of a bright portion of a video image; acquiring an average dark portion luminance corresponding to an average pixel luminance of a dark portion of the video image; generating an initial gain value of the WDR operation according to a difference between the average bright portion luminance and the average dark portion luminance; and adjusting the initial gain value according to at least one of a color temperature and an exposure duration configuration value of the video image to generate the target gain value.

Abstract: An image contrast enhancement method and an apparatus thereof are disclosed, which calculate the degree of influencing the clarity according to the influence feature (e.g., heavy fog, dust, smoke, or etc.) in the image, and then adjust the brightness of the pixels corresponding to features of influencing the clarity according to the degree, thereby enhancing image contrast and removing phenomenon of influencing the clarity in the image.

Abstract: An image-filtering device for filtering an image that includes a pixel difference computing module, an adaptive brightness adjusting module, a weighting computing module and a filter computing module is provided. The pixel difference computing module uses any one of the pixels as a central pixel within a pixel window to compute pixel absolute differences between the central pixel and every pixels within the pixel window. The adaptive brightness adjusting module multiplies each of the pixel absolute differences with an adjusting parameter to generate adjusted pixel absolute differences. The weighting computing module generates weighting values according to the adjusted pixel absolute differences. The filter computing module performs convolution according to the pixel value of each of the pixels within the pixel window and the corresponding weighting values to generate a filtering result of the central pixel.

Abstract: An image signal processing method includes: receiving an original color filter array (CFA) image and a pixel binned CFA image; computing a specific information of the pixel binned CFA image; and processing the original CFA image according to the specific information. The associated image signal processor includes an input terminal, an operating unit and a processing unit, wherein the input terminal is for receiving an original CFA image and a pixel binned CFA image, the operating unit is for computing a specific information of the pixel binned CFA image, and the processing unit is for processing the original CFA image according to the specific information and utilizing the pixel binned CFA image.

Abstract: This invention discloses an image processing device and an image processing method. The image processing device includes a line buffer, a pixel enhancing module, a smoothing module, a noise reduction module and a contrast adjusting module. The line buffer stores a plurality of pixel values of an image. The pixel enhancing module performs an edge-enhancing operation on the image. The smoothing module filters the image to improve the image in terms of roughness. The noise reduction module filters the image to improve the image in terms of a signal-to-noise ratio. The contrast adjusting module checks whether a target pixel is on a thin edge to decide the method of adjusting the contrast of the image.

Abstract: An image de-noising method and an apparatus thereof are disclosed, which includes categorizing a pixel in a current frame into a first low-frequency pixel having a first weight and a first high-frequency pixel having a second weight; categorizing a previous pixel corresponding to the position of the pixel in a previous frame into a second low-frequency pixel having a third weight and a second high-frequency pixel having a fourth weight; adjusting the first weight and the third weight and calculating the weighted sum of the first low-frequency pixel and the second low-frequency pixel, to generate low-frequency pixel data; adjusting the second weight and the fourth weight and calculating the weighted sum of the first high-frequency pixel and the second high-frequency pixel, to generate high-frequency pixel data; and calculating the sum of the low-frequency pixel data and the high-frequency pixel data, to output the de-noised pixel.

Abstract: Provided is a fast divider including an initial parameter setting unit and an arithmetic unit. The arithmetic unit is coupled to the initial parameter setting unit that receives a divisor and a dividend, and sets a plurality of initial parameters of a sequence according to the divisor and the dividend. The plurality of initial parameters includes an initial term, a first term and a common ratio having an absolute value smaller than 1. The arithmetic unit stores a recurrence relation of the sequence and iteratively computes a quotient using the recurrence relation according to the plurality of initial parameters. The recurrence relation indicates that a (k+1)th term is equal to a product of a kth term multiplied by a sum of the common ratio and 1 subtracted by a product of a (k?1)th term multiplied by the common ratio. k is an integer larger than or equal to 1.

Abstract: A lifting device configured to adjustably hold a display device at a certain height includes a support frame configured to support the display device, a shaft, a toothed gear, and a rack secured on the support frame. The shaft includes a wide portion secured on the display device and a narrow portion carrying the toothed gear, friction between the wide portion and the narrow portion being sufficient to hold the static weight of the display device. The toothed gear meshes with the rack. An upward or downward push on the display device drives the gear to move up and down along the rack to adjust the height of the display device.

Abstract: A method for generating a pixel filtering boundary required by the auto white balance (AWB) calibration is proposed. The method includes: taking a specific color temperature reference point as a center and dividing a G/B-G/R color space into six color regions having different color component relationships; based on a saturation calculating approach of a HSV color space, respectively identifying six color boundaries in the six color regions to generate a specific hexagonal filtering boundary, so that each color boundary has a predetermined saturation difference with the specific color temperature reference point; adopting the approach for generating the specific hexagonal filtering boundary to respectively identify multiple hexagonal filtering boundaries corresponding to other color temperature reference points; generating an enveloping boundary as a pixel filtering boundary based on the specific hexagonal filtering boundary and the multiple hexagonal filtering boundaries.

Abstract: A method for generating a target gain value of a wide dynamic range (WDR) operation is disclosed including: acquiring an average bright portion luminance corresponding to an average pixel luminance of a bright portion of a video image; acquiring an average dark portion luminance corresponding to an average pixel luminance of a dark portion of the video image; generating an initial gain value of the WDR operation according to a difference between the average bright portion luminance and the average dark portion luminance; and adjusting the initial gain value according to at least one of a color temperature and an exposure duration configuration value of the video image to generate the target gain value.

Abstract: A passive auto-focus device and method are disclosed herein. An embodiment of the passive auto-focus device comprises: a focus-searching-range decision circuit operable to compare a range of a variation area of a current scene with a predetermined range and determine a focus-searching range, in which the variation area is defined according to the comparison between the current scene and a preceding scene; a focal-distance-variation decision circuit operable to compare the definition pertaining to the focus-searching range with a first predetermined definition and generate a current step setting value; an image record generating circuit operable to generate first step image records in connection with the focus-searching range while the current step setting value indicates a first step and to generate second step image records in connection with the focus-searching range while the current step setting value indicates a second step, in which the first step is shorter than the second step.

Abstract: A wide dynamic range imaging method provided by an exemplary embodiment of the present disclosure has steps as follows. According to a first difference value between a light-part average luminance value and a dark-part average luminance value of an image, a first enhancing value is obtained. According to the dark-part average luminance value and a dark-part pixel number, the first enhancing value is adjusted to generate a second enhancing value. A light-part weighted average value in first regions of the image and a dark-part weighted average value in second regions of the image are calculated, a second difference value between the dark-part weighted average value and the light-part weighted average value is calculated, and the second enhancing value is adjusted to generate a third enhancing value according to the second difference value. The third enhancing value is used to selectively adjust pixels of the image.

Abstract: A method for wide dynamic range imaging is illustrated. A region mapping operation having steps as follows is applied to an image using a plurality of region mapping curves for compensating different luminance associated with a plurality of regions in the image. A low frequency image is obtained. A reference value for each region in the image is obtained according to the low frequency image. One region mapping curve is selected according to the reference value of the region. A gain curve is obtained according to the selected region mapping curve, a gain value of a pixel value or a luminance value of the region is obtained according to the gain curve, an adjusted gain value is obtained according to the luminance corresponding to the pixel value, and the pixel value is adjusted according to the luminance value, the gain value, and the adjusted gain value.

Abstract: A false color reduction system and method for color interpolation is disclosed in the present invention. The false color reduction system includes a red/blue color interpolation signal reference level estimator, a red/blue color interpolation signal noise analyzer and a red/blue color interpolation signal noise regulator. The red/blue color interpolation signal reference level estimator receives a RGB image array and a red/blue color interpolation signal of the RGB image array to generate a green difference signal. The red/blue color interpolation signal reference level estimator generates a red/blue reference level according to the green difference signal and an average signal. The red/blue color interpolation signal noise analyzer analyzes received signals to generate analysis result. The red/blue color interpolation signal noise regulator receives the analysis result to correct the red/blue color interpolation signal.

Abstract: This invention discloses an image processing device and an image processing method. The image processing device includes a line buffer, a pixel enhancing module, a smoothing module, a noise reduction module and a contrast adjusting module. The line buffer stores a plurality of pixel values of an image. The pixel enhancing module performs an edge-enhancing operation on the image. The smoothing module filters the image to improve the image in terms of roughness. The noise reduction module filters the image to improve the image in terms of a signal-to-noise ratio. The contrast adjusting module checks whether a target pixel is on a thin edge to decide the method of adjusting the contrast of the image.