Abstract: An image noise reduction device and method thereof are provided. The method includes: receiving an original image, where the original image includes a plurality of image pixels, each of the image pixels has an image pixel value and a fixed noise value, and the fixed noise value includes a decimal; obtaining a bit-shifted image pixel value, a bit-shifted fixed noise value, and a random number according to a number of bits of the decimal, the image pixel values, and the fixed noise values; obtaining a bit-shifted noise-reduced image pixel value according to the bit-shifted image pixel value, the bit-shifted fixed noise value, the random number, and a reduction equation; obtaining a noise-reduced image pixel value according to the number of bits of the decimal and the bit-shifted noise-reduced image pixel value; and obtaining a noise-reduced image according to the noise-reduced image pixel value.

Abstract: The present invention provides an image adjustment method and associated image processing circuit for performing the following operations upon each pixel of an image: obtaining R, G, B values and infrared ray (IR) value corresponding to the current pixel; generating multiple initial compensation parameters corresponding to the R, G, B values; generating an over-compensation parameter according to the R, G, B and IR values; comparing the over-compensation parameter with at least one threshold value to generate a compensation adjustment coefficient; and performing IR crosstalk compensation upon the image with the compensation adjustment coefficient.

Abstract: A method for extracting foreground image and electronic apparatus thereof is provided and implements infrared (IR) technology to perform the foreground image extraction to reduce ambient light effect and background noise. Furthermore, the method and electronic apparatus extract an IR light frame image indicating a light state, an IR dark frame image indicating a dark state, and a color image (e.g., RGB image, YUV image, or etc.) at different IR intensities. Then, the method and electronic apparatus calculate the relationship between the IR light frame image and the IR dark frame image to extract a better background image (including the user's face portion, body portion and hair portion) by a simple algorithm.

Abstract: An image adjustment method includes: receiving an image, and retrieving R, G and B values and an infrared ray (IR) value from the image; dividing the image into a plurality of blocks; generating initial compensation coefficients respectively corresponding to the R, G, B and IR values for each block within the blocks; and performing following operations upon each block within the blocks: adjusting initial compensation coefficients of a current block according to a plurality of adjacent blocks next to the current block, in order to generate adjusted compensation coefficients of the current block; and using the adjusted compensation coefficients of the current block to perform IR crosstalk compensation upon the current block.

Abstract: An image adjustment method includes: sequentially processing a plurality of pixels in at least one frame, wherein a pixel under processing is a current pixel, the current pixel and multiple adjacent pixels form a current block, and each current block is performed with following operations: reading a grayscale value of each pixel in the current block; determining a region grayscale value and a region variance of the current block according to the grayscale values of the pixels; generating a variance adjustment parameter via a variance adjustment function, wherein the region grayscale value is a variable of the variance adjustment function; generating an adjusted region variance according to the variance adjustment parameter and the region variance; and comparing the adjusted region variance with a variance threshold to determine whether to perform a noise suppression operation on the current pixel.

Abstract: Disclosed is an image processing method capable of processing facial data and non-facial data differentially. The method is carried out by an image processing device, and includes the following steps: determining a facial region, a non-facial region and a transitional region according to a face detection result of an image, in which the transitional region is between the facial region and the non-facial region; and executing different processes for the data of the facial region, the data of the non-facial region and the data of the transitional region respectively.

Abstract: An infrared crosstalk compensation method includes capturing an original image of a scene, where the original image includes a plurality of original pixels, the original pixels are arranged in a two-dimensional array according to a first axial direction and a second axial direction, and each original pixel has a red subpixel value, a green subpixel value, a blue subpixel value, and an infrared subpixel value. The method further includes: obtaining compensated values of the red, green, blue, and infrared subpixel values according to the original image, a compensation axial direction, a plurality of red, green, blue compensation coefficients corresponding to the compensation axial direction, and compensation equations; and obtaining a compensated image according to the compensated values of the red, green, blue, and infrared subpixel values.

Abstract: An image adjustment method includes: sequentially processing a plurality of pixels in at least one frame, wherein a pixel under processing is a current pixel, the current pixel and multiple adjacent pixels form a current block, and each current block is performed with following operations: reading a grayscale value of each pixel in the current block; determining a region grayscale value and a region variance of the current block according to the grayscale values of the pixels; generating a variance adjustment parameter via a variance adjustment function, wherein the region grayscale value is a variable of the variance adjustment function; generating an adjusted region variance according to the variance adjustment parameter and the region variance; and comparing the adjusted region variance with a variance threshold to determine whether to perform a noise suppression operation on the current pixel.

Abstract: A background blurred method includes steps as follows: obtaining a color image, an IR light frame image and an IR dark frame image, and calculating a differential image between the IR light frame image and the IR dark frame image to generate a binary image; obtaining a foreground image of the binary image; calculating an IR brightness mean value of the foreground image of the differential image; and filtering the color image to generate a background blurred image according to the IR brightness mean value.

Abstract: An image adjustment method includes: receiving an image, and retrieving R, G and B values and an infrared ray (IR) value from the image; dividing the image into a plurality of blocks; generating initial compensation coefficients respectively corresponding to the R, G, B and IR values for each block within the blocks; and performing following operations upon each block within the blocks: adjusting initial compensation coefficients of a current block according to a plurality of adjacent blocks next to the current block, in order to generate adjusted compensation coefficients of the current block; and using the adjusted compensation coefficients of the current block to perform IR crosstalk compensation upon the current block.

Abstract: The present invention provides an image adjustment method and associated image processing circuit for performing the following operations upon each pixel of an image: obtaining R, G, B values and infrared ray (IR) value corresponding to the current pixel; generating multiple initial compensation parameters corresponding to the R, G, B values; generating an over-compensation parameter according to the R, G, B and IR values; comparing the over-compensation parameter with at least one threshold value to generate a compensation adjustment coefficient; and performing IR crosstalk compensation upon the image with the compensation adjustment coefficient.

Abstract: An image processing method and an electronic apparatus for foreground image extraction include steps: (A) acquiring frame images of a dynamic image, wherein each frame image has an RGB image and an IR image; (B) acquiring an RGB image representing a dark state as an RGB capture image, acquiring an IR image representing a light state as an IR light frame image, and acquiring one IR image representing the dark state as an IR dark frame image; (C) calculating a difference image between the IR light frame image and the IR dark frame image and binarizing the difference image to generate a binarized image; and (D) acquiring a plurality of foreground pixels corresponding to an IR foreground part of the binarized image of the RGB capture image and taking the foreground pixels as the foreground image, thereby reducing the impact of ambient light, background noise and calculation.

Abstract: An infrared crosstalk compensation method includes capturing an original image of a scene, where the original image includes a plurality of original pixels, the original pixels are arranged in a two-dimensional array according to a first axial direction and a second axial direction, and each original pixel has a red subpixel value, a green subpixel value, a blue subpixel value, and an infrared subpixel value. The method further includes: obtaining compensated values of the red, green, blue, and infrared subpixel values according to the original image, a compensation axial direction, a plurality of red, green, blue compensation coefficients corresponding to the compensation axial direction, and compensation equations; and obtaining a compensated image according to the compensated values of the red, green, blue, and infrared subpixel values.

Abstract: A method for extracting foreground image and electronic apparatus thereof is provided and implements infrared (IR) technology to perform the foreground image extraction to reduce ambient light effect and background noise. Furthermore, the method and electronic apparatus extract an IR light frame image indicating a light state, an IR dark frame image indicating a dark state, and a color image (e.g., RGB image, YUV image, or etc.) at different IR intensities. Then, the method and electronic apparatus calculate the relationship between the IR light frame image and the IR dark frame image to extract a better background image (including the user's face portion, body portion and hair portion) by a simple algorithm.

Abstract: A background blurred method includes steps as follows: obtaining a color image, an IR light frame image and an IR dark frame image, and calculating a differential image between the IR light frame image and the IR dark frame image to generate a binary image; obtaining a foreground image of the binary image; calculating an IR brightness mean value of the foreground image of the differential image; and filtering the color image to generate a background blurred image according to the IR brightness mean value.

Abstract: Disclosed is an image processing method capable of processing facial data and non-facial data differentially. The method is carried out by an image processing device, and includes the following steps: determining a facial region, a non-facial region and a transitional region according to a face detection result of an image, in which the transitional region is between the facial region and the non-facial region; and executing different processes for the data of the facial region, the data of the non-facial region and the data of the transitional region respectively.

Abstract: An image processing method and an electronic apparatus for foreground image extraction include steps: (A) acquiring frame images of a dynamic image, wherein each frame image has an RGB image and an IR image; (B) acquiring an RGB image representing a dark state as an RGB capture image, acquiring an IR image representing a light state as an IR light frame image, and acquiring one IR image representing the dark state as an IR dark frame image; (C) calculating a difference image between the IR light frame image and the IR dark frame image and binarizing the difference image to generate a binarized image; and (D) acquiring a plurality of foreground pixels corresponding to an IR foreground part of the binarized image of the RGB capture image and taking the foreground pixels as the foreground image, thereby reducing the impact of ambient light, background noise and calculation.