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.

该研究提出了一种将多重焦点图像融合在无线视觉传感器网络中的算法，该算法利用离散余弦变换标准来确定融合标准，利用空间频率和一致性验证过程提高输出图像质量，并在多对多重焦点图像上进行测试，结果显示提高了输出图像的视觉质量并超越了其他基于DCT的技术。

基于空间频率和DCT域一致性验证的多焦点图像融合