Fast pairwise nearest neighbor based algorithm for multilevel thresholding

Abstract

We propose a fast pairwise nearest neighbor (PNN)based O(N log N) time algorithm for multilevel nonparametric thresholding, where N denotes the size of the image histogram. The proposed PNN-based multilevel thresholding algorithm is considerably faster than optimal thresholding. On a set of 8 to 16 bits-per-pixel real images, experimental results also reveal that the proposed method provides better quality than the Lloyd-Max quantizer alone. Since the time complexity of the proposed thresholding algorithm is log linear, it is applicable in real-time image processing applications.

Detecting and tracking regional outliers in meteorological data

“…Even though this is a very good result, it is far from a log linear algorithm. A nearest neighbor based algorithm for finding the thresholds was proposed in [48], with a time complexity of O(n log n).…”

Hybrid Genetic Algorithmdan Ant Colony Optimizationuntuk Optimisasi Metode Multilevel Image Thresholding

“…Seperti dalam [3], fungsi Otsu dimodifikasi untuk dapat dioptimasi dengan algoritma fast recursive. Metode lain dengan pairwise nearest neighbour sebelumnya digunakan dalam hierarchical clustering yang diadaptasi untuk melakukan multilevel clustering [4]. Dari semua threshold yang mungkin, salah satu threshold yang meningkatkan nilai fungsi objektif digunakan.…”

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