Image processing method for UAV aerial photography
An image processing and unmanned aerial vehicle technology, applied in the field of image processing, can solve the problems of affecting the quality of image compression, reducing the theoretical limit entropy, and obtaining an accurate reference for predictive coding. The effect of increasing the bandwidth compression ratio
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Embodiment 1
[0052] See figure 1 , figure 1 A flow chart of an image processing method for aerial photography of a drone provided in an embodiment of the present invention, the method includes the following steps:
[0053] Step 1, using the UAV image acquisition device to collect the image in real time to generate an image data source;
[0054] Step 2, establishing an adaptation method for the UAV image data source compression interface;
[0055] Step 3, compressing the image data source to generate a digital transmission signal of the image data source;
[0056]Step 4: Send the digital transmission signal to the control terminal on the ground; and convert it into an image display.
[0057] Among them, the H.264 video compression coding standard can only compress the information in its own specific format, while the image and video information collected by the drone has a variety of formats, such as multi-frame video information, hyperspectral images, SAR images, etc., through The adap...
Embodiment 2
[0085] Specifically, see figure 2 , figure 2 It is a flowchart of an adaptive template prediction method provided by an embodiment of the present invention. This embodiment introduces in detail the adaptive template prediction method proposed by the present invention on the basis of the above embodiments, and the prediction method includes the following steps:
[0086] Step 1. Create and update an adaptive template
[0087] See image 3 , image 3 It is a schematic diagram of an adaptive template provided by an embodiment of the present invention. The establishment of the adaptive template includes the following steps:
[0088] Step 11, define the number of epitopes and the sequence number of epitopes of the adaptive template
[0089] Preferably, the number of epitopes in the adaptive template can be defined as 16; the number of epitopes in the adaptive template is 16, and the epitope numbers are arranged in order from 0 to 15. The smaller the sequence number, the high...
Embodiment 3
[0118] See Figure 4 , Figure 4 It is a flow chart of another prediction method for an adaptive template provided by an embodiment of the present invention. The forecasting method includes the following steps:
[0119] Step 1. Update the adaptive template corresponding to the current MB; see step 13 of the embodiment for details
[0120] Step 2. Adaptive prediction
[0121] After the adaptive template is updated, the pixel value of the current MB and all existing MB reconstruction values in the adaptive template are used for adaptive texture prediction to solve the prediction residual.
[0122] Among them, see Figure 5 , Figure 5 A schematic diagram of adjacent reference pixels for adaptive texture prediction provided by an embodiment of the present invention. Select the reference pixels in the adaptive texture prediction, A, B, C, E are the surrounding pixels adjacent to the current pixel, that is, the reconstruction value corresponding to the current pixel in any ...
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