Coded data processing method and device, computer equipment and storage medium
A technology of encoding data and processing methods, which is applied in digital video signal modification, electrical components, image communication, etc., can solve the problems of low bit rate control efficiency and waste of resources, and achieve the effect of saving resources and improving video bit rate control efficiency
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Embodiment 1
[0030] figure 1 It is a schematic flow chart of the encoding data processing method provided in Embodiment 1 of the present application. This embodiment is applicable to the case of video encoding data processing. This method can be performed by a video encoder, or by providing preprocessing for video encoding. The device execution of the data, the video encoder or the aforementioned device can be located in the server or the user terminal, and the method specifically includes the following steps:
[0031] Step 110: Perform target area detection on the target image to obtain the target area.
[0032] The target image is any frame picture in the video coding data. Any frame in the video stream can be read before encoding, and the frame is the target image. Each target image is processed separately to achieve the effect of optimizing the coding strategy.
[0033] Optionally, when the target frame picture is obtained, the target area may be identified using an ROI identificati...
Embodiment 2
[0047] figure 2 A schematic flowchart of a method for processing encoded data provided in Embodiment 2 of the present application, as a further description of the above embodiment, includes:
[0048] Step 210: Perform target area detection on the target image to obtain the target area.
[0049] Step 220, blurring the target image to obtain a blurred image.
[0050] When enhancing the image, step 220 and step 230 can refer to the Unsharp MaskingTechnique algorithm provided by "Image Edge Enhancement AndDenoising Techniques For Computer Vision Applications". This algorithm applies the blur kernel (Gaussian kernel, box) to the target image to obtain a blurred image, and finally superimposes the difference image on the original image to obtain an enhanced image
[0051] Step 230. Determine a difference image according to the target image and the blurred image.
[0052] After the blurred image is obtained in step 220, the target image is subtracted from the blurred image to obt...
Embodiment 3
[0065] image 3 A schematic flowchart of a method for processing encoded data provided in Embodiment 2 of the present application, as a further description of the above embodiment, includes:
[0066] Step 310: Perform target area detection on the target image to obtain the target area.
[0067] Step 320, acquiring edge data of the target area.
[0068] Step 330, configuring a first quantization offset value for the first pixel, where the first pixel is a pixel outside the target area, and the first quantization offset value is greater than zero.
[0069] After the edge data is obtained by using the difference image, the first pixel point and the second pixel point can be distinguished. The first pixel is a pixel outside the target area.
[0070] A quantization offset table (qp offset table) can be designed to record the quantization offset value of each pixel. For the live scene, fill the positive quantization offset value in the background area in the quantization offset ...
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