Adaptive Image Encoding with Dynamic Codec Selection
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Solution Overview
Problem
Existing video compression methods struggle to efficiently manage storage space and image quality when encoding video data, particularly when the available storage space is unknown at the start of encoding, leading to potential overflow or unnecessary degradation.
Innovation Solution
A method that dynamically selects codecs based on a remaining bit budget and loss measures, allowing transitions between different lossy and lossless codecs without constraints, ensuring the encoded image fits within the available storage while maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single lossless codec is used for all pixels, then image quality is maximized, but storage space consumption increases and may overflow the buffer
Solution Approach 1:
The patent applies local quality by selecting different codecs for different pixels based on their individual characteristics and the remaining bit budget. Each pixel can be encoded with an appropriate codec (lossless or lossy) rather than applying a uniform codec to the entire image, thus optimizing both quality and storage space locally for each pixel region.
Solution Approach 2:
The patent changes the codec parameter dynamically based on the remaining bit budget and pixel characteristics. The system transitions between lossless and lossy codec modes by adjusting the encoding parameter, allowing flexible adaptation to storage constraints while maintaining optimal image quality where possible.
2Quantity of substance
If a single lossy codec is used for all pixels, then storage space is reduced, but image quality degrades significantly
Solution Approach 1:
The patent applies local quality by selectively applying lossless encoding to specific pixels that require higher quality preservation while using lossy encoding for other pixels where quality degradation is acceptable. This localized approach ensures that critical regions maintain high quality while non-critical regions contribute to overall compression.
Solution Approach 2:
The patent uses partial action by applying lossless encoding only to the extent necessary based on the remaining bit budget and image requirements. Rather than applying lossless encoding universally, it partially applies it only where needed, thereby optimizing the balance between storage space and image quality.
3Stability of the object's composition
If codec selection is constrained to prevent frequent transitions, then encoding stability improves, but adaptability to bit budget changes decreases
Solution Approach 1:
The patent implements dynamics by allowing the codec selection to change dynamically from pixel to pixel based on the remaining bit budget and image characteristics. The system is designed to be adaptive, transitioning between lossless and lossy modes as needed, rather than being static or constrained to fixed codec sequences.
Solution Approach 2:
The patent uses preliminary action by calculating the remaining bit budget in advance and using it to guide codec selection for subsequent pixels. This preliminary calculation allows the system to proactively adjust codec choices to ensure the encoded image fits within the available storage space while maintaining quality where possible.
4Quantity of substance
If lossy encoding is applied early in the image, then bit budget is conserved for later pixels, but early pixel quality degrades
Solution Approach 1:
The patent applies local quality by determining the appropriate codec for each pixel based on its specific characteristics and the remaining bit budget. Early pixels that are visually critical can be encoded with lossless codecs to preserve quality, while less critical early pixels can use lossy encoding to conserve bits for later regions.
Solution Approach 2:
The patent uses feedback by continuously monitoring the remaining bit budget and adjusting codec selection accordingly. The system receives feedback about the current encoding state and adapts its codec choices for subsequent pixels to ensure optimal use of the available bit budget while maintaining overall image quality.
Data Source
AI summary
A system and method for encoding an image. The method includes: encoding a first pixel of an image using a first codec; selecting, based on a remaining bit budget, a second codec; encoding a second pixel, immediately following the first pixel, using the second codec, wherein: the first codec has a first loss, according to a measure of loss; and the second codec has a second loss, according to the measure of loss, the second loss being greater than zero and less than the first loss.