Abstract: An image processing method includes: performing a first division on an acquired preprocessed image to obtain a plurality of first sub-image regions; when it is determined that image parameters of the plurality of first sub-image regions do not meet a first preset condition, performing a second division on the plurality of first sub-image regions, to obtain a plurality of second sub-image regions; performing attribute identification on each second sub-image region of the plurality of second sub-image regions to obtain an identification attribute of each second sub-image region; according to an image processing method corresponding to the identification attribute of each second sub-image region, performing image processing on the second sub-image region to obtain a third sub-image region; and merging a plurality of third sub-image regions to obtain a target image.

Abstract: Provided is a method for correcting image density, an image forming device, a control device and a system. The method includes: in response to an image density correcting instruction triggered by a user, forming an image density pattern for image density correcting; collecting image density data corresponding to the image density pattern; generating (tone reproduction curve) TRC data according to the image density data corresponding to the image density pattern; sending the TRC data to a control device. The control device is configured to correct image density based on the TRC data during the image forming process. The user controls the device for image forming to generate the TRC data in advance and sends the TRC data to the control device. During the image forming process, the control device can directly use the TRC data for image density correction, thereby improving image forming efficiency and user experience.

Abstract: Provided is an image calibration method, an image formation device and a storage medium. The image calibration method includes: acquiring at least one of a first end color density value or a second end color density value of a calibration reference image along a direction to be calibrated; calculating a difference between the at least one of the first end color density value or the second end color density value and a target color density value, to obtain at least one of a first end color density difference value or a second end color density difference value; and performing uniformity calibration on an image to be calibrated if the at least one of the first end color density difference value or the second end color density difference value is greater than or equal to a preset difference threshold.

Abstract: The present disclosure provides a color enhancement method, an image-forming apparatus and a storage medium. The method includes dividing color band data to-be-processed into a plurality of color blocks; counting a quantity of exposure points of each color channel of each color block in an apparatus color space, and generating an exposure point distribution image corresponding to each color block; converting the exposure point distribution image into a color image in a preset color space; calculating a color feature value corresponding to each color block according to the color image in the preset color space; and determining whether the color block needs image enhancement; and if the color block needs the image enhancement, modifying a weight of each color channel in the apparatus color space according to the color feature value, and outputting modified data of each color channel according to the modified weight of each color channel.

Abstract: Provided is an image calibration method, an image formation device and a storage medium. The image calibration method includes: acquiring at least one of a first end color density value or a second end color density value of a calibration reference image along a direction to be calibrated; calculating a difference between the at least one of the first end color density value or the second end color density value and a target color density value, to obtain at least one of a first end color density difference value or a second end color density difference value; and performing uniformity calibration on an image to be calibrated if the at least one of the first end color density difference value or the second end color density difference value is greater than or equal to a preset difference threshold.

Abstract: An image processing method, applied to an electronic apparatus, includes performing feature extraction processing on a source image to obtain a feature data set corresponding to a source file, determining an image processing parameter corresponding to the feature data set according to the feature data set, and processing the source image according to the image processing parameter.

Abstract: An image processing method, an image forming apparatus, and a storage medium are provided in embodiments of the present disclosure. The image processing method includes acquiring a first color component value and a second color component value of each pixel of a to-be-processed image in a preset color space; determining a color cast pixel according to the first color component value and the second color component value of each pixel; and performing pixel correction on each color cast pixel to obtain a corrected to-be-processed image. In the technical solutions of various embodiment of the present application, the color cast pixel in the to-be-processed image is determined by the first color component value and the second color component value of the pixel, and the pixel correction is performed on the color cast pixel, which removes colored noise in the printed image and improves image printing quality.

Abstract: Method, device, and storage medium for image processing, and apparatus for image formation are provided. The method includes obtaining original image data and detecting a tilt angle of an image according to the original image data. The method also includes performing a binarization processing on the original image data to obtain binarized image data. The binarization processing and detecting the tilt angle are performed in parallel. Further, the method includes performing a rotation correction on the binarized image data according to the detected tilt angle.

Abstract: An image processing method is provided. The method includes acquiring image data; obtaining a page pixel average value of the image data; acquiring image processing parameters based on the page pixel average value; obtaining a pixel processing threshold by a calculation based on at least a first portion of the image processing parameters; based on the pixel processing threshold, adjusting a pixel value of a current pixel of the image data by using at least a second portion of the image processing parameters; and outputting an adjusted image according to the adjusted pixel value of the current pixel of the image data.

Abstract: Method and device for image rotation, and apparatus for image formation are provided. The method includes obtaining a tilt angle and size information of a to-be-processed image data, and obtaining position information of a target pixel corresponding to each rotated original pixel by performing a calculation based on the tilt angle and the size information and position information of each original pixel. The method also includes obtaining an enhancement parameter value and an edge parameter value by filtering the original pixel. Further, the method includes performing a two-dimensional interpolation process based on neighboring pixels of the original pixel, the enhancement parameter value and the edge parameter value, and obtaining a target pixel value of the target pixel according to an original pixel value of the original pixel, the enhancement parameter value, and the edge parameter value, thereby obtaining a target image corresponding to the rotated to-be-processed image data.

Abstract: A text separation method, a text separation device, and an image formation apparatus are provided. The text separation method includes obtaining a pixel value of each pixel in a to-be-processed image having a plurality of pixels; determining an edge intensity value of each pixel according to pixel values of each pixel and a preset number of pixels adjacent to each pixel; determining a binary map corresponding to the to-be-processed image according to the edge intensity value of each pixel; determining a text region determination value of each pixel according to the binary image and the pixel value of each pixel; and determining text-body regions and non-text-body regions in the to-be-processed image according to the text region determination value of each pixel.

Abstract: Method, device, and storage medium for image processing, and apparatus for image formation are provided. The method includes obtaining original image data and detecting a tilt angle of an image according to the original image data. The method also includes performing a binarization processing on the original image data to obtain binarized image data. The binarization processing and detecting the tilt angle are performed in parallel. Further, the method includes performing a rotation correction on the binarized image data according to the detected tilt angle.

Abstract: An image processing method is provided. The method includes acquiring image data; obtaining a page pixel average value of the image data; acquiring image processing parameters based on the page pixel average value; obtaining a pixel processing threshold by a calculation based on at least a first portion of the image processing parameters; based on the pixel processing threshold, adjusting a pixel value of a current pixel of the image data by using at least a second portion of the image processing parameters; and outputting an adjusted image according to the adjusted pixel value of the current pixel of the image data.

Abstract: Method and device for image rotation, and apparatus for image formation are provided. The method includes obtaining a tilt angle and size information of a to-be-processed image data, and obtaining position information of a target pixel corresponding to each rotated original pixel by performing a calculation based on the tilt angle and the size information and position information of each original pixel. The method also includes obtaining an enhancement parameter value and an edge parameter value by filtering the original pixel. Further, the method includes performing a two-dimensional interpolation process based on neighboring pixels of the original pixel, the enhancement parameter value and the edge parameter value, and obtaining a target pixel value of the target pixel according to an original pixel value of the original pixel, the enhancement parameter value, and the edge parameter value, thereby obtaining a target image corresponding to the rotated to-be-processed image data.

Abstract: A text separation method, a text separation device, and an image formation apparatus are provided. The text separation method includes obtaining a pixel value of each pixel in a to-be-processed image having a plurality of pixels; determining an edge intensity value of each pixel according to pixel values of each pixel and a preset number of pixels adjacent to each pixel; determining a binary map corresponding to the to-be-processed image according to the edge intensity value of each pixel; determining a text region determination value of each pixel according to the binary image and the pixel value of each pixel; and determining text-body regions and non-text-body regions in the to-be-processed image according to the text region determination value of each pixel.

Abstract: In various embodiments, an image processing method using self-adaptive error diffusion algorithm, a related apparatus and device are provided. In some embodiments, the method comprises: determining a neighboring region in an original image for error diffusion process, the neighboring region including a center point and its adjacent points; based on pixel values of the center point and the adjacent points, calculating an error diffusion process weight value for each adjacent point corresponding to an error diffusion process from the center point towards each adjacent point; after binarizing the pixel value of the center point, calculating an error value according to the binarized pixel value of the center point; adding a product of the error diffusion process weight value for each adjacent point and the error value to the pixel value of each adjacent point respectively to obtain an error-diffusion-processed pixel value for each adjacent point in the neighboring region.