Abstract: A method and electronic apparatus for image matching, including: determining matching area in image according to where search frame is located in the image; calculating average gray-scale value of pixels in each column/row in the matching area, calculating average gray-scale value of pixels in the matching area in any consecutive columns/rows corresponding to the quantity of the columns/rows in any one of the pre-built template samples, calculating similarity between the average gray-scale value of the pixels in the matching area and average gray-scale value of the pixels in columns/rows of the template sample, and taking the template sample having the maximum similarity as an image matching template sample. Therefore, the traditional process of assembling collected images together is removed for preventing the problem in matching imprecisely. The process of assembling images is removed by several independent template samples, so the result of image matching is precise.

Abstract: Disclosed in the present disclosure is a method and an electronic apparatus for identifying video characteristic, wherein, the method includes the following steps: acquiring a video sample to be identified; extracting all key frames of the video sample; classifying the plurality of key frames of the video sample using a deep learning model; and determining whether the video to be identified is a salacious video according to a classification result. Therefore, videos regarding salacity could be identified in a video library. As a result, operating risks are reduced and financial and human resources are saved.

Abstract: Disclosed are a transcoding method and electronic apparatus. The method includes: obtaining 16 H.264 video macro blocks; determining encoding type of the 16 H.264 video macro blocks; transcoding the 16 H.264 video macro blocks into a H.265 coding tree unit CTU according to preset intra-frame transcoding correspondence if the encoding type of the 16 H.264 video macro blocks is intra-frame coding; transcoding the 16 H.264 video macro blocks into one H.265 CTU according to preset inter-frame transcoding correspondence if the encoding type of the 16 H.264 video macro blocks is inter-frame coding. The device includes: capturing module, determination module, first transcoding module and second transcoding module. The present invention has no need to decode H.264 video macro blocks to produce original video data, so the transcoding process can speed up and save time.

Abstract: Disclosed are a method and an electronic apparatus for identifying and coding animated video. By dimensionally reducing a video to be identified, obtain an input characteristic parameter of the video to be identified; by invoking a characteristic model trained in advanced according to the input characteristic parameter, determine whether the video to be identified is an animated video; and when it is determined the video to be identified is the animated video, adjust a coding parameter and a bit rate of the video to be identified. The bandwidth is saved and the coding efficiency is raised in the situation that high resolution video is obtained.

Abstract: The embodiment of the present disclosure discloses an image sharpening method and based on gradient value and gradient direction and an electronic apparatus thereof. Scan pixel points in an image one by one and calculate gradients of the pixel points; sharpen the pixel points if determine the gradient is larger than a predetermined gradient threshold value, update pixel values of the pixel points with pixel values obtained from the sharpening. Effectively eliminate the perceptible gray scale mutation and also self-adaptively adjust the degree of the image sharpening.

Abstract: Embodiments of the present disclosure provide a method and electronic apparatus for processing image data, including: taking an inserted pixel as a center point, determining neighbor pixel; obtaining gradient magnitudes and directions of each neighbor pixel; calculating correlations between each neighbor pixel and the center point; calculating the gradient magnitudes of each neighbor pixel and the correlations between the neighbor pixel and the center point to obtain gray scale of the center point which is gray scale of the inserted pixel; taking the other inserted pixels each as a center point to obtain gray scale thereof, and determining color of each inserted pixel according to all the gray scales of the inserted pixels, and obtaining an image with increased image resolution by fully considering the patterns and features of the image, so it can maintain original patterns and features of the original image to become more vivid and natural.

Abstract: The embodiments of the present invention provide a method and a device video denoising and detail enhancement. The method includes: acquiring the pixel value of a current pixel in a frame as a first pixel value, and acquiring the pixel values of adjacent pixels in the up, down, left and right sides of the current pixel; denoising the current pixel to acquire the second pixel value of the current pixel; determining whether the current pixel is a detail pixel; and if the current pixel is determined as the detail pixel, calculating the detail pixel value of the current pixel according to the first pixel value and the second pixel value, and using the detail pixel value to update the first pixel value. The present invention implements effective denoising, and reserves and enhances the image details of a video frame in the meanwhile.

Abstract: The embodiment of the present disclosure discloses a video transcoding method and a video transcoding device, used for solving the problems in the prior art that a user cannot clearly watch video content during watching and the user experience is reduced because the content of the sampled screen video is vague. The method comprises the following steps: recognizing an original video, and determining whether the original video is a screen video; and transcoding the original video according to a resolution ratio of the original video if the original video is the screen video. According to the embodiment of the present disclosure, the screen video does not need to be sampled, and the content of the transcoded video is not vague, so that the user can clearly watch the video content during watching.

Abstract: The embodiments of the present invention provide a method for adaptive spatial-domain video denoising, including: acquiring the pixel value of each pixel at the same positions of a current frame and a previous adjacent frame thereof so as to calculate the noise intensity of the current pixel; and acquiring the pixel values of adjacent pixels in the up, down, left and right sides of the current pixel in a current frame respectively, calculating the denoising weights of the current pixel and the adjacent pixels in the up, down, left and right sides according to the noise intensity, the pixel value of the current pixel and the pixel values of the adjacent pixels in the up, down, left and right sides, and using a value acquired through weighted average to replace the pixel value of the current pixel so as to maximally reserve frame details while implementing the adaptive spatial-domain denoising of the current pixel.

Abstract: The embodiment of the present disclosure provides a method for removing video watermarks, wherein the method includes: finding out a watermark region in a video and selecting a proper watermark expansion region, and copying the pixels of the watermark expansion region to form a mask region; extending the watermark region in an original video frame to form a stuffing region, and using pixels beside the stuffing region to stuff the watermark region to acquire a video frame after stuffing; and performing blur processing on the mask region, and finally superposing the video frame after stuffing with the mask region after blur processing, thus being capable of removing the watermarks completely, and ensuring the smooth transition between the watermark-removed region and a surrounding region in the meanwhile