A Feature Extraction Using SIFT with a Preprocessing by Adding CLAHE Algorithm to Enhance Image Histograms
Raul David Palma Olvera, Elizabeth Martinez Zeron, Jesús Carlos Pedraza‐Ortega, Juan Manuel Ramos Arreguín, Efrén Gorrostieta Hurtado · 2014
In this paper a novel method is proposed to improve the performance of the SIFT (Scale Invariant Feature Transformation) algorithm in adverse illumination conditions (in an outdoor environment at night), for this research it is proposed to work with CLAHE (Contrast Limited Adaptive Histogram Equalization), adding a preprocessing stage to the traditional methodology of the SIFT algorithm, this will be applied to the building to be found in the scene, i.e., the image pattern. A comparison with different illumination conditions (day, evening and night) will be held to know the response that will have the SIFT algorithm and to identify which moment the algorithm has a better performance.