Source data acquisition and compression method for wireless projection

Abstract

The invention discloses a source data acquisition and compression method for wireless projection, which belongs to the field of wireless projection. The method can quickly and efficiently capture and compress screen images, transmits the compressed screen images to a service terminal for display via a wireless network, and finally achieves the function of wireless projection. The scheme adopts screenshot based on mirror image driving and an optimization algorithm based on H.264. Compared with the traditional screenshot GDI and DirectX, the method has the advantages of low occupancy of CPU, high quality of images, high efficiency of screenshot and the like. Aiming to the characteristic of the large interframe relativity of the screen images, the video compression algorithm based on the H.264 is improved, and on the basis, layered codes based on ROI (Region of Interest) is introduced, and as a result, the data transmission capacity is lower and the quality is higher.

Description

technical field [0001] The present invention relates to a method for realizing wireless projection technology, and more specifically, the present invention mainly relates to a method for collecting and compressing information source data for wireless projection. Background technique [0002] In a projection system, the source is the screen image. Screen data collection technologies mainly include GDI screen capture and DirectX screen capture. The GDI screenshot mechanism is based on the simple common sense that "the desktop is also a window, and the desktop also has a window handle". If we get the device context (DC) of the desktop, we can use it to copy its content to the DC we created. . To get the handle of the window, the function GetDeskWindow() can be used. Similarly, DC can also be obtained through the handle HWnd. The specific implementation method is: 1. Obtain the desktop handle through the GetDesktopWindow() function; 2. Obtain the desktop DC with GetDC(); 3. ...

AI Technical Summary

Problems solved by technology

However, the defect of j peg2000 is that the algorithm only compresses one picture, and in the process of projection, it needs to continuously capture the client screen image for compression. The previous frame and the next frame of a frame of image are likely to be similar, which means strong inter-frame correlation

If the jpeg2000 algorithm is used, the efficiency of image compression for each frame is obviously not high

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