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Image Bit-Depth Enhancement via Maximum A Posteriori Estimation of AC Signal
Summary
This study addresses image bit-depth enhancement by estimating missing bits for higher quality rendering. A novel two-step method improves image quality significantly compared to existing techniques.
Area of Science:
- Computer Vision
- Image Processing
- Signal Processing
Background:
- Rendering low bit-depth images on high bit-depth displays requires estimating missing least significant bits.
- The image bit-depth enhancement problem involves reconstructing an original image from its quantized version.
Purpose of the Study:
- To develop an efficient and effective method for image bit-depth enhancement.
- To estimate the original image from a quantized version using a minimum mean squared error (MMSE) perspective.
Main Methods:
- Utilizing a graph-signal smoothness prior defined on a graph embedding image structure.
- Proposing an efficient approximation strategy by estimating the ac component via maximum a posteriori (MAP) using convex programming.
- Computing the dc component using an MMSE criterion in closed form, given the estimated ac component.
Main Results:
- The proposed two-step approach provides improved performance over conventional bit-depth enhancement schemes.
- Experiments demonstrate superior objective and subjective comparisons for the new method.
Conclusions:
- The graph-signal smoothness prior is suitable for image bit-depth enhancement.
- The efficient two-step approximation strategy effectively solves the computationally expensive MMSE problem for bit-depth enhancement.
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