61 results about "Image colorization" patented technology

The invention discloses a gray level image colorization system and method based on a GLCM. The gray level image colorization system comprises an image block module, a GLCM feature extraction module, a similarity matching establishment corresponding relation module, a color marking and preliminary correction module and an optimization coloring module. The deficiencies of previous methods can be overcome, and engineering practice requirements are met. According to the method, the image colorization speed can be increased and the image colorization effect can be improved.

The invention discloses a similar image colorization algorithm based on classification learning. The similar image colorization algorithm comprises the following steps: sample images are collected, an image gradation co-occurrence matrix attribute is extracted, the sample images are classified into five categories through the AP algorithm, superpixels of a target image and superpixels of a reference image are calculated respectively, then, colors are transferred from the reference image to the target image, colors of the superpixels are corrected afterwards according to continuity of image space, and finally the algorithm is used for conducting color diffusion to complete colorization. According to the similar image colorization algorithm, the influence on an image by a global attribute of the image is considered, the image gradation co-occurrence matrix attribute is extracted to conduct classification learning on parameters of a superpixel matching function, as a result, different parametric functions can be provided for superpixel matching on images with different compositions, and the universality of the similar image colorization algorithm on the images is improved; besides, after the matching process, region growing algorithm partition can be conducted at a superpixel level, and color correction can be conducted in a region.

The invention discloses a two-way colorization method for animation images based on a U-shaped periodic consistent confrontation network, relating to the Image processing field, Data collection, pixels of the animation illustration image are unified; A training data set and a test data set are constructed, finally, the capacities of a generator G, a generator F, a discriminating network DX and a discriminating network DY are improved by adopting a cyclic training method with consistent U-shaped periods, a function mapping relation between an image and a color image is found, and bidirectionalconversion of a black-white sketch and a full-color image is realized. According to the method, the features do not need to be extracted manually, a training set does not need to be marked, the workload of a cartoon creator is remarkably reduced, the image colorization and blackening processing efficiency is improved, and great help is provided for the cartoon creator.

A liquid composition which can achieve superior scratch resistance of images at such a level that coloring materials are hardly scraped off even when images are scratched with finger nails under application of such strong pressure as to scratch a recording medium at its non-recorded areas. The liquid composition contains at least a modified siloxane compound having specific structure and a polymer whose acid value and hydrogen bond parameter (δh) are specified.

The invention discloses a method for intelligently coloring a microstructure photo shot by an electron microscope and a CNN coloring learner, and the method comprises the following steps of firstly, manufacturing a data set which is a set of a plurality of color SEM images, and learning the data set by a shader; converting a to-be-colored microscopic grayscale photo shot by the electron microscope as an input image into an LAB color space, and intercepting a grayscale image with a pixel size of H*W from the microscopic grayscale photo as an input image XL of a CNN; coloring the shader. According to the present invention, the coloring process of the present invention needs to additionally provide a color image in real life similar to the texture structure of a gray image with a colored target as a reference image, and the end-to-end black box type training is conducted on the convolutional neural network, so that the manual participation is not needed.

The invention discloses a document image processing method and device, and the method comprises the steps: carrying out the image denoising processing of an RGB document image through a negative noisethree-channel color relation, and obtaining a denoised document image; based on the minimum bounding rectangle of each foreground connected region in the denoised document image, obtaining a target rotation direction and a target rotation angle by using a preset correction rule, and performing image correction on the denoised document image to obtain a corrected document image; and for the correction document image, performing image coloring processing and image trimming processing through background three-channel clustering in combination with the RGB document image to obtain a target document image. Visibly, the image processing effect of the RGB document image is improved from the aspects of image denoising, image correction, image coloring and image trimming, and the image processingrequirement of the RGB document image is met.

The invention discloses an image colorization method and system and a computer readable storage medium. The method comprises the following steps: A, converting an image to be colorized from an RGB color space to a YUV color space, and separating Y channel data; B, copying the Y channel data, and constructing two-channel data together with the Y channel data; C, using the data of the two channels as the input of a depth convolution auto-encoder to predict UV channels respectively, wherein the depth convolution auto-encoder is formed by connecting a plurality of rejump layers; D, combining the Ychannel data with the UV channel data predicted in the step C to construct a complete YUV color space image; and E, converting the YUV color space image into an RGB color space image to obtain a final colorized image. According to the method, the problems of model gradient disappearance and over-fitting can be better solved, a better coloring effect and better image definition are achieved, artifacts generated by the image can be effectively reduced, and the color saturation can be effectively enhanced.

The invention discloses a grayscale image colorization method based on a generative adversarial network, and the method comprises the steps: firstly, selecting a quantitative color image group in a COCO image data set, carrying out the decoloring processing, making a training set, constructing a generative adversarial network architecture, enabling a generator model to complete the pre-training in the generative adversarial network architecture, and carrying out the image colorization. And then alternately training the discriminant model and the pre-trained generative model, adjusting parameters to obtain a trained model, and inputting test data into the model to realize gray level image colorization. Through the pre-training method and process of the generator, the training method and data set optimization are greatly improved, the training time is greatly shortened on the basis of ensuring the training quality and the generalization quality of the finally generated image, and the method has flexibility; and training and testing are carried out on a COCO data set by utilizing a U-Net thought, so that the defects that manual intervention is needed and fine coloring work of a large-size image pixel level is difficult to carry out in a traditional method can be reduced to a great extent.

The invention discloses a method for editing propagation of video and image content based on local feature structure preservation, comprising: mapping all pixels in the input original image and / or video key frames to a selected feature space; finding K nearest neighbor pixels for each pixel according to feature vectors' Euclidean distance in the selected feature space; using Locally Linear Embedding (LLE) dimension reduction to construct the locally linear relationship between each pixel and its K nearest neighbor pixels in the selected feature space; According to the present invention, it is possible to accurately perform such image or video processing as automatic color transformation, interactive color editing, gray image colorization, video cloning and image matting.

In an image processor, images are created, stored, manipulated and regenerated using color tinting, where color tinting applies component-to-color mapping from a color card to a plurality of component images, which are then combined to form a final image, tinted according to the content of the color card. In some instances, the color card might code one color for each of N components, in which case the final image might be the merging of each of N monochromatic component images colored by the color coded by the color card. In other instances, the color card codes for intensity levels or a texture.