Abstract

Dark-field scattering imaging is an imaging method with high contrast and high sensitivity. It has been widely employed in optical components evaluation, biomedical detection, semiconductor manufacturing, etc. However, useless background information causes data redundancy, which increases unnecessary time-space costs in processing. Furthermore, the problem is particularly serious in high-resolution imaging systems for large-aperture components. The dark-field scattering image compression (DFSIC) based on the compressed sparse row is proposed to solve this problem. The compression method realizes local data access for a sparse matrix. The result of the experiments shows that the average time-space consumption of the DFSIC is reduced to less than 2%, compared with the raw image structure, and is still kept below 68% in dense cases. This method provides a more efficient program implementation for the dark-field scattering imaging and exhibits potential in the application of the optical detection with large scale.

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