Speeding up the Köhler's method of contrast thresholding
This work addresses the speed limitations of a multi-thresholding technique for image and video processing applications, representing an incremental improvement.
The paper tackled the high computational complexity of Köhler's contrast thresholding method by introducing a new algorithm with reduced complexity from O(N^2) to O(N M), enabling a gain factor of 405 for an 18-million-pixel image and real-time video processing with a gain factor of 96.
K{ö}hler's method is a useful multi-thresholding technique based on boundary contrast. However, the direct algorithm has a too high complexity-O(N 2) i.e. quadratic with the pixel numbers N-to process images at a sufficient speed for practical applications. In this paper, a new algorithm to speed up K{ö}hler's method is introduced with a complexity in O(N M), M is the number of grey levels. The proposed algorithm is designed for parallelisation and vector processing , which are available in current processors, using OpenMP (Open Multi-Processing) and SIMD instructions (Single Instruction on Multiple Data). A fast implementation allows a gain factor of 405 in an image of 18 million pixels and a video processing in real time (gain factor of 96).