  Multi-focus is a technique of focusing on different aspects of a particular
object or scene. Wireless Visual Sensor Networks (WVSN) use multi-focus image
fusion, which combines two or more images to create a more accurate output
image that describes the scene better than any individual input image. WVSN has
various applications, including video surveillance, monitoring, and tracking.
Therefore, a high-level analysis of these networks can benefit Biometrics. This
paper introduces an algorithm that utilizes discrete cosine transform (DCT)
standards to fuse multi-focus images in WVSNs. The spatial frequency (SF) of
the corresponding blocks from the source images determines the fusion
criterion. The blocks with higher spatial frequencies make up the DCT
presentation of the fused image, and the Consistency Verification (CV)
procedure is used to enhance the output image quality. The proposed fusion
method was tested on multiple pairs of multi-focus images coded on JPEG
standard to evaluate the fusion performance, and the results indicate that it
improves the visual quality of the output image and outperforms other DCT-based
techniques.

Computer Vision and Pattern Recognition