Inter-frame coding unit size division method based on neural network
A coding unit and inter-frame coding technology, which is applied in the field of inter-frame coding, can solve problems such as high dependence, increased partition complexity, and serious consumption of computing resources, and achieve the effect of reducing complexity and data dependence
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Embodiment 1
[0049] This embodiment implements a neural network-based inter-coding unit size division method, such as figure 1 shown, including the following steps:
[0050] S1. Obtain a coding unit of a first preset size;
[0051] S2. Input the coding unit into the trained neural network model to obtain a coding unit of a second preset size;
[0052] S3. Record the size of the coding unit of the second preset size, find its corresponding position in the model prediction result, and perform summing and averaging operation to obtain the probability of not dividing the coding unit;
[0053] S4. Calculate the probability of dividing the coding unit into sub-blocks, and then perform a summing and averaging operation back to the size of the coding unit to obtain the probability of the coding unit of the second preset size in the current division mode;
[0054] S5. Obtain the preset number of probabilities, compare and sort them, and select the division modes corresponding to the top N highest...
Embodiment 2
[0071] This implementation implements a neural network-based inter-coding unit size division method, including the following steps:
[0072] Step 1. Obtain a coding unit of a first preset size.
[0073] In this embodiment, the coding unit (CU) size of the first preset size is selected as 64x64.
[0074] Step 2. Input the coding unit into the trained neural network model to obtain a coding unit of a second preset size.
[0075] In this embodiment, the second preset coding unit (CU) size is selected to be 16x16x22 for output.
[0076] Step 3. Record the size of the coding unit of the second preset size, find its corresponding position in the model prediction result and perform summing and averaging operation to obtain the probability of not dividing the coding unit.
[0077] The general process of training the neural network model is still as follows image 3 As shown, the specific training steps are as follows:
[0078] obtain samples;
[0079] Dividing the sample into a t...
Embodiment 3
[0094] This embodiment implements an AVS3 hardware encoder, and the AVS3 hardware encoder applies the neural network-based inter-frame coding unit size division method in any of the foregoing implementation manners. The neural network-based inter-coding unit size division method includes the following steps:
[0095] Obtain a coding unit of a first preset size;
[0096] Inputting the coding unit into the trained neural network model to obtain a coding unit of a second preset size;
[0097] Recording the size of the coding unit of the second preset size, finding its corresponding position in the model prediction result and performing the summing and averaging operation to obtain the probability of not dividing the coding unit;
[0098] calculating the probability of dividing the coding unit into sub-blocks, and then performing a summing and averaging operation back to the size of the coding unit to obtain the probability of the coding unit of the second preset size in the curr...
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