Open AccessA DWT Based Novel Multimodal Image Fusion Method
Author(s) -
Sumanth Kumar Panguluri,
Laavanya Mohan
Publication year - 2021
Publication title -
traitement du signal/ts. traitement du signal
Language(s) - English
Resource type - Journals
eISSN - 1958-5608
pISSN - 0765-0019
DOI - 10.18280/ts.380308
Subject(s) - image fusion , artificial intelligence , computer vision , computer science , enhanced data rates for gsm evolution , image (mathematics) , fusion , filter (signal processing) , contrast (vision) , fusion rules , image processing , pattern recognition (psychology) , philosophy , linguistics
Nowadays multimodal image fusion has been majorly utilized as an important processing tool in various image related applications. For capturing useful information different sensors have been developed. Mainly such sensors are infrared (IR) image sensor and visible (VI) image sensor. Fusing both these sensors provides better and accurate scene information. The major application areas where this fused image has been mostly used are military, surveillance, and remote sensing. For better identification of targets and to understand overall scene information, the fused image has to provide better contrast and more edge information. This paper introduces a novel multimodal image fusion method mainly for improving contrast and as well as edge information. Primary step of this algorithm is to resize source images. The 3×3 sharpen filter and morphology hat transform are applied separately on resized IR image and VI image. DWT transform has been used to produce "low-frequency" and "high-frequency" sub-bands. "Filters based mean-weighted fusion rule" and "Filters based max-weighted fusion rule" are newly introduced in this algorithm for combining "low-frequency" sub-bands and "high-frequency" sub-bands respectively. Fused image reconstruction is done with IDWT. Proposed method has outperformed and shown improved results in subjective manner and objectively than similar existing techniques.