Objective As highresolution image sensors and computer technology develop, significant applications for holography have emerged in the fields of threedimensional imaging and display, optical information processing, and intelligent optical computing. However, numerous challenges remain unresolved in both digital holography and computational holography.During the recording process of digital holography, as a kind of multiplicative noise, speckle noise becomes a prominent problem and its removal is more challenging than that of additive noise, drastically compromising the quality of the reconstructed image. Consequently, noise reduction in holograms and reconstructed images is of particular urgency.Current noise reduction methods are primarily categorized into two categories: opticalbased methods and digitalbased methods. In the opticalbased methods, one limitation involves the cumbersome recording process of multiple holograms with speckle diversity by multiple mechanical motions, which could lower the system stability. In the digitalbased methods, complex algorithm commonly reaches better noise reduction effects. However, the cost of increased processing time may impede the realtime capability of the system. Therefore, an integrated approach combining optical and digital methods can maximize noise reduction while maintaining a focus on speed. Therefore, we combine Fourier transform spectroscopy technology and digital holography technology to gain speckle diversity holograms. Then, utilizing the noise difference analysis of decrypted images at several wavelengths, we propose a weighted summation average (WSA) noise reduction method, in combination with the block matching 3D (BM3D) algorithm. As a result, the optimized effect of noise
