Quasi-Noise-Free and Detail-Preserved Digital Holographic Reconstruction

Abstract

The shortcoming of the coherence of digital holographic light sources leads to the generation of holographic reconstruction speckle noise, which seriously affects the quality of holographic reconstruction. Although many advanced algorithms for reducing speckle noise in digital holography (DH) have achieved good results, in the process of processing image speckle noise, the details of the image are blurred, and the information relating to the image texture is lost. Therefore, we propose a new algorithm, which combines automatic GrabCut and guided filtering to solve the problem of blurred image details in filtering reconstruction. The new algorithm is applied to the problem of holographic speckle removal for the first time. In this paper, the new algorithm not only achieves quasi-noise-free (approximate the noise-free state) DH reconstruction but also realizes the retention of details in the image. The quality of the resulting holographic reconstruction is comparable to that achieved by incoherent technology, which exceeds the current level of DH and produces a good visual effect. INDEX TERMS Holography, guided filtering, automatic GrabCut, noise.

Advances in Digital Holographic Interferometry

“…A solution is proposed in the form of using a combination of the Grab-Cut algorithm–the selection of an object from the background–with a controlled filtering algorithm. The result is a quasi-noiseless reconstructed image [ 63 ].…”

An optical-digital method of noise suppression in digital holography

“…There are various approaches to improve the quality of reconstructed images from digital holograms. They can be divided into two main groups: numerical methods (image processing) [30,[46][47][48][49][50][51][52][53][54] and optical solutions [55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71]. Numerical methods are based on digital filters and/or iterative procedures, most often involving the processing of two-dimenionsal (2D) objects.…”

“…To suppress these negative factors, numerical methods (image processing) [30,[46][47][48][49][50][51][52][53][54] and optical [55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70] solutions have been developed. Numerical methods are usually based on digital filters and/or iterative procedures, such as average value subtraction [46], median filtering [47], window frequency filters [48], non-linear filtering of a single quadrant [49], wavelet filter [50], Lee and Frost filters [51], meanmedian filtering [52], non-local means [53], block matching 3D (BM3D) filtering [54], etc [30]. Simple filters usually use averaging or a non-iterative transformation.…”

“…Various filters can be used as a 3D filter. For example, non-local averaging can be chosen (Lee or Frost filters [51], non-local means [53], etc). In this work, a median filter is chosen as the basis for 3D filtering, since it has a number of important properties: it is easy to implement, windowed, and non-linear compared to an averaging filter, which is used in multi-look methods.…”

A Virtual Optical Holographic Encryption System Using Expanded Diffie-Hellman Algorithm

“…However, a long size encryption key will create another problem which will reduce the speed of the encryption process. The optical encryption technology based on holographic has emerge as a new technology that has many has many advantages such as high speed, high capacity and is multi-dimensional as well [1][2][3]. For these reasons, the optical holographic encryption technology is gradually received great attention and considered as an enabling technology [4,5].…”