Improved median spatial filtering algorithm: A reduced temporal complexity approach

Autor: Diana Teresa Gómez Forero, Julian Dario Miranda Calle
Rok vydání: 2016
Předmět:
Zdroj: 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA).
DOI: 10.1109/stsiva.2016.7743311
Popis: When capturing images in real environments, there's an incidence of external and internal adverse factors. These factors can cause negative changes in the captured graphical results. By implementing enhancement techniques used in digital image processing, it is possible to achieve an output of greater detail and an attenuation of affectation components. An algorithmic proposal for median spatial filtering that decreases the temporal complexity from the Matlab classical spatial median filtering algorithm, by means of experimental and analytical behavior of the specific spatial median filtering algorithm is presented. Upon completion of these procedures, and executing the improved median filtering algorithm with graphical test data, the results showed that the input images were similarly improved, incident graphic noise components were attenuated and the execution times decreased.
Databáze: OpenAIRE