Abstract: A method includes building a driver model in frequency domain, extracting S (scattering) parameters, the S parameters to describe a real curve that represents a real signal channel between the driver model and a load circuit, and generating, based on the extracted S parameters, an approaching curve of the real curve, the approaching curve being expressed in an approaching equation.

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: 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 method includes building a driver model in frequency domain, extracting S (scattering) parameters, the S parameters to describe a real curve that represents a real signal channel between the driver model and a load circuit, and generating, based on the extracted S parameters, an approaching curve of the real curve, the approaching curve being expressed in an approaching equation.

Abstract: Provided is a handheld electronic apparatus, a touch sensor, and a touch detection method thereof. The touch sensor includes a substrate, a strain gauge, a plurality of piezo sensors, and a touch layer. The substrate has a first surface and a second surface opposite to the first surface. The strain gauge is disposed on the first surface of the substrate. The piezo sensors are disposed on the second surface. The touch layer covers a plurality of piezo sensors and the strain gauge.

Abstract: A handheld electronic apparatus includes a housing, a plurality of touch sensors, and a controller. The controller under power saving mode activates parts of touch sensors to execute a touch detection action.

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 method includes providing a symbolic power distribution network (PDN) map for a PDN of an circuit design including at least a first mesh that includes a plurality of map nodes; modeling at least one parasitic component that is provided on a branch of the symbolic PDN map and a pair of current sources that are provided at two respective map nodes of the symbolic PDN map; providing a matrix equation based on an interrelated conduction behavior among the parasitic component and the pair of current sources, wherein the matrix equation includes a current source term representing the pair of current sources and an unknown variable term representing a voltage level of at least a map node of the symbolic PDN map; and based on the matrix equation, expanding the unknown variable term in a frequency-domain as a sum of plural mathematical components while keeping the current source term intact.

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 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: 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: 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 process for preparing aryl ketones is disclosed. The process includes photo-oxidizing a compound of formula (V), (VI), (VII) or (VIII): in the presence of an oxidative system comprising at least one bromide compound to form aryl ketones. X1, X2, R1, R2, R3, L1, L2, L3, L4, t, n, m and p have the meanings as described in the specification and claims.

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: 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 correction method arranged for processing an original image to obtain a corrected image includes steps: receiving the original image from an image sensor; regarding each pixel of the original image, calculating a horizontal distance and a vertical distance between the pixel and a reference point in the original image; determining a horizontal ratio parameter and a vertical ratio parameter according to the horizontal distance and the vertical distance between the pixel and the reference point in the original image; and performing an approximately non-linear regression calculation on the horizontal ratio parameter, the vertical ratio parameter and a coordinate of the pixel to obtain a position of the pixel in the corrected image.