Scalable Video Encoding Weighted Motion Prediction Brightness Variation
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Solution Overview
Problem
Conventional video encoding methods, such as H.264/AVC and JSVC, face challenges in performing weighted motion prediction when brightness varies non-uniformly within a slice or nonlinearly over time, leading to degraded prediction performance due to limitations in calculating appropriate weight coefficients, especially in cases like fade images or images with flashes.
Innovation Solution
A video scalable encoding method that generates weight coefficients based on temporal brightness variation between a decoded signal of a reference frame and an immediately-lower layer of an encoding target frame, allowing for weighted motion prediction without transmitting weight coefficient information, thereby enabling precise prediction even in cases of nonlinear brightness changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional motion prediction is performed by block-matching based on minimization of pixel value difference, then encoding performance is enhanced for standard images, but prediction residual increases by an amount equivalent to brightness variation for images with temporal brightness changes
Solution Approach 1:
The patent applies parameter changes by introducing weight coefficients (w0, w1) and offset coefficients (d0, d1) to modify the motion prediction formula. Instead of using simple block-matching, the invention transforms the prediction equation to z = w0·r0 + d0 and z = w1·r1 + d1, where the coefficients are calculated based on temporal brightness variation. This parameter transformation allows the prediction to adapt to brightness changes, reducing prediction residual while maintaining encoding efficiency.
2Measurement precision
If explicit mode weighted motion prediction is used to transmit weight coefficients, then prediction performance is improved, but encoding amount increases due to transmission of weight coefficient information
Solution Approach 1:
The patent extracts the weight coefficient calculation from the encoding process and performs it independently based on temporal brightness variation analysis. By separating the coefficient calculation (which depends only on reference frame brightness) from the motion prediction process, the invention eliminates the need to transmit weight coefficients while maintaining prediction accuracy. The decoder can independently reproduce the same coefficients using the same brightness variation analysis.
3Quantity of substance
If implicit mode weighted motion prediction is used to avoid transmitting weight coefficients, then encoding amount is reduced, but prediction performance degrades when brightness varies non-uniformly within a slice or nonlinearly over time
Solution Approach 1:
The patent applies local quality by calculating weight coefficients for each block rather than uniformly for the entire slice. The coefficients w0 and w1 are determined based on the temporal brightness variation of each specific block, allowing different regions with different brightness characteristics to have customized prediction parameters. This block-level adaptation enables the implicit mode to handle non-uniform and nonlinear brightness variations effectively.
4Ease of manufacture
If conventional implicit mode calculates weight coefficients based only on reference frame information, then encoding is simplified, but appropriate weight coefficients cannot be calculated for nonlinear brightness variation
Solution Approach 1:
The patent applies preliminary action by pre-calculating the temporal brightness variation between reference frames before performing motion prediction. The weight coefficients are determined in advance based on the brightness characteristics of the reference frames, and these pre-calculated coefficients are then used in the motion prediction process. This preliminary calculation ensures that the coefficients are optimized for the specific brightness conditions without adding complexity to the main encoding flow.
Data Source
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AI summary
A video scalable encoding method calculates a weight coefficient which includes a proportional coefficient and an offset coefficient and indicates brightness variation between an encoding target image region and a reference image region in an upper layer, calculates a motion vector by applying the weight coefficient to an image signal of a reference image region as a search target and executing motion estimation, and generates a prediction signal by applying the weight coefficient to a decoded signal of a reference image region indicated by the motion vector and executing motion compensation. Based on encoding information of an immediately-lower image region in an immediately-lower layer, which is present at spatially the same position as the encoding target image region, a data structure of the weight coefficient is determined. When the immediately-lower image region performed interframe prediction in the immediately-lower layer, the method identifies an immediately-lower layer reference image region that the immediately-lower image region used as a prediction reference for motion prediction, and calculates the weight coefficient by applying a weight coefficient that the immediately-lower image region used in weighted motion prediction to a DC component of an image region in the upper layer, which is present at spatially the same position as the immediately-lower layer reference image region, and assuming a result of the application as a DC component of the immediately-lower image region.