Microscopy Depth of Field Extension via Multi-Pass Image Blending
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Solution Overview
Problem
Existing methods for improving depth of field in microscopy are inefficient due to high computational complexity and poor performance, failing to effectively capture the entire specimen in focus with a single image.
Innovation Solution
A method and apparatus that combine a sequence of digital images captured at different focal distances to form a single all-focus image by computing a focus measure at every pixel, finding candidate values, and blending them according to the focus measure to determine final pixel values, thereby reducing a large stack of microscopy images to a single or smaller all-focus image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If existing methods for improving depth of field are used, then depth of field is extended, but computational complexity becomes too high
Solution Approach 1:
The patent divides the image processing task into multiple passes: first computing a rough depth map with coarse resolution, then refining it with higher resolution. This segmentation of the computational task reduces the overall complexity by breaking down the single complex operation into simpler sequential steps that can be processed more efficiently.
Solution Approach 2:
The patent introduces an intermediate depth map as a mediator between the input images and the final output. This intermediate representation stores depth information that can be reused across multiple pixels, avoiding redundant computations. The depth map acts as a cache that mediates between the raw image data and the final composite image, significantly reducing computational complexity.
2Manufacturing precision
If existing methods for improving depth of field are used, then depth of field is extended, but processing performance becomes poor
Solution Approach 1:
The processing is segmented into distinct phases: depth map computation, candidate selection, and final composite generation. This allows the system to process images in an optimized pipeline where each stage can be independently optimized, improving overall processing performance while maintaining extended depth of field quality.
Solution Approach 2:
The patent performs preliminary computation of the depth map before generating the final composite image. This preliminary action identifies which pixels from which source images should be used, allowing the final composition step to simply copy pixels rather than perform complex optimizations. This preliminary analysis dramatically improves processing performance.
3Loss of information
If a large stack of microscopy images is captured, then complete specimen coverage is achieved, but data volume increases significantly
Solution Approach 1:
The patent extracts only the essential depth information from the large stack of images into a compact depth map representation. Instead of storing and processing all original images, the system extracts depth values for each pixel and uses this condensed representation to generate the final composite image, significantly reducing data volume while preserving complete specimen coverage information.
Solution Approach 2:
The patent creates a simplified copy of the depth information in the form of a depth map, which is much smaller than the original image stack. This depth map copy contains all necessary information to reconstruct the extended depth of field image without requiring the full original data, achieving efficient data reduction while maintaining information completeness.
Data Source
AI summary
A method for improving depth for field (DOF) in microscopic imaging, the method comprising combining a sequence of images captured from different focal distances to form an all-focus image, comprising computing a focus measure at every pixel, finding the largest peaks at each position in the focus measure as multiple candidate values and blending the multiple candidates values according to the focus measure to determine the all-focus image.