Low Complexity Compression and Speed Enhancement for Optical Scanning Holography

Abstract

In this paper we report a low complexity compression method that is suitable for compact optical scanning holography (OSH) systems with different optical settings. Our proposed method can be divided into 2 major parts. First, an automatic decision maker is applied to select the rows of holographic pixels to be scanned. This process enhances the speed of acquiring a hologram, and also lowers the data rate. Second, each row of down-sampled pixels is converted into a one-bit representation with delta modulation (DM). Existing DM-based hologram compression techniques suffers from the disadvantage that a core parameter, commonly known as the step size, has to be determined in advance. However, the correct value of the step size for compressing each row of hologram is dependent on the dynamic range of the pixels, which could deviate significantly with the object scene, as well as OSH systems with different opical settings. We have overcome this problem by incorporating a dynamic step-size adjustment scheme. The proposed method is applied in the compression of holograms that are acquired with 2 different OSH systems, demonstrating a compression ratio of over two orders of magnitude, while preserving favorable fidelity on the reconstructed images.

Computational Optical Scanning Holography

“…The time to obtain holograms of OSH is limited by the scanning speed of the FZP due to single-pixel detection [31], although recent IDH techniques with an image sensor can record moving targets with the framerate [32][33][34]. While OSH possesses the disadvantage of low measurement speeds, many kinds of undersampling methods have been proposed [35][36][37][38]. Interestingly, OSH also obtains holograms under a coherently illuminated condition by using a pinhole in front of a detector [39][40][41][42].…”

Wavelet compression of off-axis digital holograms using real/imaginary and amplitude/phase parts

“…The different methods of compressing holographic image or video files 10–13 can be divided into three main groups based on the following:image and video compression standards (JPEG, HEVC, etc.) 13–20 , including additional HEVC-coding optimization 18 and neural network post-processing 19 ;vector and scalar methods of quantization (iterative or noniterative) 10,21–29 , including phase-difference-based implementation 28 and local and global thresholding binarization 29 ; andwavelet transforms 11,30–41 , including the cosine transform 32,33 and the Fresnelet transform 34 .However, several other compression methods can be considered separately from the above-mentioned groups: for example, scanning methods 33,42 and generative approaches 43 . A number of methods can be assigned to different groups of techniques also.…”

“…However, several other compression methods can be considered separately from the above-mentioned groups: for example, scanning methods 33,42 and generative approaches 43 . A number of methods can be assigned to different groups of techniques also.…”

Incoherent Digital Holography: A Review

“…On the basis of a similar concept, not only the vertical pixel pitch but also the horizontal pixel pitch can be adjusted dynamically. In compressive optical scanning holography (COSH) [57,73], only a portion of the hologram pixels of a row are selected and converted into a 1-bit binary representation. Therefore, the resulting hologram data size can be about 1% of that of the original hologram.…”