Multi-focus image fusion using VOL and EOL in DCT domain

TL;DR

This paper introduces a novel multi-focus image fusion method in the DCT domain using VOL and EOL as contrast measures, improving block selection accuracy and resulting in higher quality fused images.

Contribution

The paper proposes a new approach for calculating Laplacian-based contrast measures directly in DCT domain, reducing errors in block selection for image fusion.

Findings

Enhanced image quality compared to previous methods

Reduced errors in block selection during fusion

Effective in processing JPEG multi-focus images

Abstract

The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focused images are captured with different depths of focus of cameras. Multi-focus image fusion is very time-saving and appropriate in discrete cosine transform (DCT) domain, especially when JPEG images are used in visual sensor networks (VSN). The previous works in DCT domain have some errors in selection of the suitable divided blocks according to their criterion for measurement of the block contrast. In this paper, we used variance of Laplacian (VOL) and energy of Laplacian (EOL) as criterion to measure the contrast of image. Also in this paper, the EOL and VOL calculations directly in DCT domain are prepared using vector processing. We developed four matrices which calculate the Laplacian of block easily in DCT domain. Our works greatly reduce error due to unsuitable block selection. The results of the proposed algorithms are compared with the previous algorithms in order to demonstrate the superiority of the output image quality in the proposed methods. The several JPEG multi-focus images are used in experiments and their fused image by our proposed methods and the other algorithms are compared with different measurement criteria.