Digital speckle reduction: a comparison between methods

Speckle noise reduction by multiple reconstructions in digital off axis holography

Digital holography (Yamaguchi & Zhang, 1997; Osten et al., 2002; Kreis, 2005; Ferraro et al., 2005; Frauel et al., 2006; Nomura & Imbe, 2010) is a useful technique for recording the fully complex field of a wavefront. In line with advances in imaging devices such as CCDs, digital holography is accessible. The digital holography has been used for lots of applications including encryption (Javidi & Nomura, 2000; Tajauerce & Javidi, 2000; Nomura et al., 2004) and three-dimensional object recognition (Poon & Kim, 1999; Tajauerce et al., 2001; Javidi & Kim, 2005). However, the quality of a reconstructed image of a digital hologram is not good, because it is suffering from speckles. Comparing a conventional film hologram, the extent of a digital hologram is small and the resolution of the hologram is low in single figure. This is why the reconstructed image has noticeable speckles. To reduce the speckles, some signal processing approaches have been proposed (Javidi et al., 2005; Do et al., 2005; Maycock et al., 2005; Kreis & Schluter, 2007). By use of wavelet decomposition, three-dimensional image fusion has been proposed and some speckles reduction has been achieved. Independent component analysis has been also applied to reduce speckles. Aperture synthesis approach is also proposed to enhance the resolution. Somewhat speckle noises have been reduced by the approaches. In this paper, two methods to reduce speckle of the reconstructed image are presented. One is the method based on the superposition of the reconstructed images with different wavelengths. Another is the method based on the multiple holograms. In Section 2, the characteristics of speckles are reviewed briefly. In Section 3, the former method is described. Some experimental results are shown to confirm the proposed method. In Section 4, the latter method is described with some experimental results for confirmation.

A gray-level intensity image can be employed as a host image for hiding a watermark image to protect information security. Past research works demonstrate that a gray-level hidden image can be embedded into the host image by a digital phase-only holography method. However, the fidelity of retrieved watermark image from the host image is not very satisfactory and the host image quality is degraded due to the insertion of external data bits, especially when observers focus on the saliency regions in the host image. To address this problem, we propose a steganography method based on digital holography and the saliency map of the host image. First, we calculate the hidden capacity (number of bits to be replaced) for each host image pixel based on the weighted sum of pixel intensity and saliency value. Next, a multilevel phase-only digital hologram of the watermark image will be calculated by the Gerchberg–Saxton method under the constraint of the hidden capacity of host image. Finally, we embedded the multilevel phase-only digital hologram into the host image by replacing a corresponding number of bits in each pixel. In this way, the host image can preserve good image fidelity for its saliency regions even if we hide a large amount of digital hologram data into the host image. The experimental results show that the quality of retrieved watermark image from the host image and the quality of saliency regions in the watermarked host image, in our proposed scheme, are superior to the state-of-the-art works reported.

A speckle noise suppression method in digital holography is proposed by the angular diversity with a phase-only spatial light modulator (SLM). The minimal angular difference of illumination beams is quantitatively analyzed to ensure the noncorrelation of any two speckle patterns, and then the phase-only SLM is employed to generate a series of tilted illumination beams. Comparing with the typical methods, the tilted illumination beams are controlled dynamically and accurately, which makes it possible to record a large number of holograms. Finally, using an image-plane digital holographic system, 117 holograms are recorded respectively, and the synthesized reconstructed images are obtained with the greatly suppressed speckle noise which is in good agreement with the theoretical results. The experimental results demonstrate the effectiveness, repeatability, and practicability of the proposed approach.

In this thesis, fundamental concepts of holographic reconstruction are applied to enhance the imaging process of marine plankton. Digital holography is relevant in this context as it allows the refocusing of particles and organisms at different planes of the optical path, thereby increasing the imaged volume while maintaining detailed structures of interest for automatic classification. In the first section of this work, a focus metric called image quality (Q) is proposed and comparatively evaluated, estimated based on numerical simulation and experimental data obtained in the laboratory through the combination of three focus functions. A second component of this research assessed the applicability of the focus criterion (Q) in plankton studies. Samples prepared with different concentrations of live organisms were filmed using an in-line digital holography system. After segmentation and reconstruction using the Q index as the autofocus criterion, the number of organisms detected per holography was compared with counts under a stereomicroscope. The study showed a high linear agreement between the two methods, indicating that the use of digital holography in combination with the Q estimate is reliable for plankton quantification. A third study was conducted to determine the best focus criterion among a total of 18 functions, considering different taxonomic groups, organism morphology, and camera sensor characteristics. The definition function (D) performed well, but the Q function generated lower average error in all tested situations, standing out as the most efficient function for holographic reconstruction of planktonic organisms. The application of the Q function in in situ holograms was tested with data generated by a submersible digital holography system in the northern Gulf of Mexico. The holograms were segmented and reconstructed using the Q function for subsequent automatic classification. The concentration of particles and organisms obtained from the holograms was evaluated in relation to density, temperature, salinity, and chlorophyll along the water column to determine vertical distribution. Thin layers of phytoplankton were detected near the picnocline/halocline, in a region of high stratification and vertical stability. The phytoplankton was dominated by diatom species (Chaetoceros debilis, Chaetoceros socialis, and other centric diatoms). Colonies of C. socialis and chains of C. debilis showed multiple concentration peaks, with the absolute maximum coinciding with the thin layers. Zooplankton was dominated by Copepoda and gelatinous organisms (Chaetognatha and Appendicularia), observed in higher concentration usually above the picnocline. Heterogeneous zooplankton aggregations were recorded throughout the water column. The set of studies conducted in this work laid the groundwork for improving the hologram autofocus process and confirmed the potential application of digital holography techniques in marine plankton research.

Speckle noise inherent to synthetic aperture radar (SAR) imagery degrades image quality and complicates automated analysis in Earth observation applications. Quantitative assessment of despeckling results requires computing quality metrics against reference images, which are unavailable in operational SAR scenarios. This paper presents a method for a priori prediction of filtered Sentinel-1 SAR image quality metrics before applying speckle noise filters. Unlike existing approaches predicting relative quality improvement, the proposed method predicts absolute values of five metrics (PSNR, WSNR, SSIM, MS-SSIM, FSIM) for a specific filter, enabling direct comparison and rational filter selection. The methodology employs transfer learning of DenseNet-121 convolutional neural network, pre-trained on ImageNet, adapted for single-channel SAR inputs through architectural modifications including input layer transformation, pooling optimization, and regression head replacement. A novel synthetic data generation pipeline utilizes histogram matching of Sentinel-2 optical images with Sentinel-1 SAR references to create training samples preserving ground truth. Dynamic gamma-distributed speckle noise addition with variable ENL ∈ [2, 6] enhances data variability and model robustness. Experiments with six classical filters (Gamma MAP, Lee, Enhanced Lee, Frost, SRAD, Kuan) demonstrate high prediction accuracy across all filter-metric combinations. The coefficient of determination R² reaches 0.997 for best combinations and exceeds 0.97 for most of the 30 trained models. Mean absolute prediction errors remain below 0.29 dB for PSNR and 0.014 for SSIM across all tested configurations. The approach enables a priori quality prediction without reference images, allowing optimization of SAR processing workflows and resource planning before resource-intensive despeckling. Contributions of Authors: Conceptualization, Raed A. and Oleksii R.; methodology, Raed A.; formal analysis, Raed A.; investigation, Raed A. and Oleksii R.; data curation, Raed A. and Oleksii R.; writing—original draft preparation, Raed A.; writing—review and editing, Raed A. and Oleksii R.; visualization, Raed A. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Data Availability Statement: The processed dataset is available in the Zenodo repository (https://zenodo.org/uploads/17253925). Python implementation code is available in the GitHub repository (https://github.com/rsenaikh/Predicting_Quality_after_Noise_Removal). Acknowledgments: The authors would like to express their sincere gratitude to the Copernicus Data Space Ecosystem for providing open access to Sentinel-1 and Sentinel-2 data. We are also grateful to reviewers and editors for their valuable comments, recommendations, and attention to the work. Conflicts of Interest: The authors declare no conflict of interest.

In this review, we introduce digital holographic techniques and recent progress in multidimensional sensing by using digital holography. Digital holography is an interferometric imaging technique that does not require an imaging lens and can be used to perform simultaneous imaging of multidimensional information, such as three-dimensional structure, dynamics, quantitative phase, multiple wavelengths and polarization state of light. The technique can also obtain a holographic image of nonlinear light and a three-dimensional image of incoherent light with a single-shot exposure. The holographic recording ability of this technique has enabled a variety of applications.

Digital Holography (DH) suffers from severe degradation of the reconstruction quality due to the presence of speckles. Speckle is due to the source coherence and shows on the hologram as a multiplicative, correlated noise. Due to the larger size of the speckle grains, the lower resolution, and the worse features of the available hardware, long wavelength digital holography is more severely degraded by noise than its visible wavelength counterpart is. Non-Bayesian approaches to the denoising problem suffer from resolution loss or complex acquisition systems required to record multiple uncorrelated holograms to be averaged. Instead of providing multiple captures, these can be simulated to yield a number of reconstructions from one single hologram (generally referred to as numerical Multi-Look, ML). However, the ML improvement is inherently bounded to a theoretical limit. On the other hand, image processing has offered a wide literature on the topic over the last decades. Among the most efficient methods to reduce additive Gaussian noise, 3D Block Matching (BM3D) has emerged and it is nowadays widely used in the image processing framework. However, BM3D performance worsens in the presence of speckle and cannot be effectively applied to long wavelength DH. Here we show that the joint action of numerical ML (thought as a preprocessing filter) and BM3D in post-processing permits to overcome the theoretical limit of ML and to outperform the BM3D for the denoising of holograms. The quasi noise free reconstruction of long wavelength holograms of famous artworks will be shown.

Particle Image Velocimetry PIV has been widely adopted in many areas of science and engineering for measuring the flow in fluids, and the pseudo flow, translational motion, in solids. In both applications, fluids and solids, the necessity for the presence of particles has been solved by the introduction of particles in the samples being monitored. The interference in the sample by the physical introduction of particles can be considered therefore a drawback of this methodology. In solids in particular, it is possible to overcome that drawback by providing a laser speckle pattern image on a solid surface, thereby mimicking the external particles needed in the correlation of the images during the PIV implementation. In fluids this possibility also arises, and in this work we present an approach to associate laser biospeckle to PIV analysis in fluids in the complete absence of external particles. Biospeckle, which is a term used to characterize the dynamic laser speckle, is the phenomenon that occurs when we illuminate a sample which shows dynamic change of its laser light scatterers. The difference in applications to fluids is related to the boiling effect of the speckle grains which in solids will behave in pure translational movements that will not occur with the dynamic speckle in the flow of fluids. The boiling effect in the flow of fluids has the translational movements but also the random boiling effect observed in the biospeckle. The challenge was then to isolate the translational contribution of the speckle grains and use them as a reference to PIV. The experiment was done using water and gel in a known flow, illuminated by a 632nm laser beam. The biospeckle images collected were processed in order to filter the signal and isolate the information related to the translational motion of the fluid. A collection of images at different times were filtered using the wavelet transform, with the PIV being carried on in the range of frequencies linked to the translation of the fluid. The results demonstrated the potential application of the proposed approach, which needs some thorough adjustments depending on the fluid under analysis. The methodology presents high sensitivity to the velocity of the flow, to the size of the grains, and to the density of the fluid proving itself to be better used in micro-flows.

Digital holography is practical technique for researching of 3D-objects parameters. There are various limitations of reconstructed image quality: speckle noise, twin image, zero order, shot noise, camera's fixed pattern noise (FPN). In this work comparison of effect of digital camera's main noise components on hologram reconstruction is investigated. Characteristics of different type's cameras were used. It was obtained that for majority of cameras shot noise has higher effect on reconstructed images. However for various conditions FPN alone result in worse reconstruction quality than shot noise does. Borders of equal effect of shot noise and FPN on reconstructed images were obtained.

In digital holography, the speckle noise caused by the coherent nature of the light source and the light scattering generated by the light path system degrade the quality of the reconstructed image seriously. Therefore, in this paper, we propose what we believe to be is a novel noise reduction method combining bidimensional empirical mode decomposition (BEMD) with the variational method, termed BEMDV. The reconstructed image is first decomposed into a series of bidimensional intrinsic mode function (BIMF) components with different frequencies using the BEMD method, and then a certain number of BIMF components are selected for noise reduction by the variational method. An improved particle swarm optimization algorithm is adopted to optimize the key parameters of the proposed method, so as to further improve its noise reduction performance. A reflective off-axis digital holographic imaging system is used to collect the holograms of the coin and optical resolution plate, and the experimental research on noise reduction is carried out. The results with qualitative and quantitative analyses show that the proposed method achieves a better performance on noise reduction and detail preservation than other general methods, enormously enhancing the image quality of holographic reconstruction.

Multi-wavelength digital holography is a very powerful approach for surface shape measurements. It has the advantage of being contact-less, non-intrusive, and yields full-field surface shape data without any requirement for scanning. When dealing with off-axis digital holography and spatial multiplexing of two-wavelength digital holograms, the method becomes real-time, in the sense that the surface shape can be measured at each time instant at which the holograms are recorded. Thus, phase shifting and sequential recording are suppressed. However, due to the roughness of the inspected surface, speckle decorrelation occurs and noise is included in the final data. The noise amount in the data must be investigated in order to define the best processing approach for holograms. This paper proposes the analysis of the standard deviation of noise in surface-shape data from two-wavelength spatially-multiplexed digital holograms. The influence of noise on the measurements of the surface shape is described by an analytical approach. Relationships to quantify the minimum measurable surface height is given by taking into account the experimental parameters of the set-up. These parameters are related to the spatial bandwidths, modulation of holograms, saturation ratio, number of electrons in pixels, readout noise, quantization noise, photon noise, and speckle decorrelation due to roughness. The theoretical modeling is discussed and analysis when considering practical situation for industrial surface shape measurements.

The Optica Digital Holography and Three-Dimensional Imaging Topical Meeting (DH) 2024 in Paestum, Italy, brought together a vibrant hub for global experts to showcase cutting-edge research and industry pioneers to discuss the latest developments in digital holography (DH) and 3D imaging techniques. This meeting's impact is further amplified by a dedicated feature issue across three prestigious Optica journals: Applied Optics, Journal of the Optical Society of America A, and Biomedical Optics Express. This introduction summarizes the diverse and high-quality contributions, highlighting key advancements and applications that are shaping the future of DH and imaging.

The detection of crack on materials is an important issue in industry. On the contrary to conventional methods, such as manual inspection, sensor detection, and image processing techniques, a new simple method to detect the crack is proposed with optical voice recorder based on digital holography in this paper. Holograms obtained with sound waves passing through the materials are recorded by using the digital holography technique. Temporal behavior of the sound wave passing through the material, which is obtained from these holograms, gives image of crack. In this article, cracks in various materials are determined by the proposed new method, and crack images obtained with this new system are presented.

We demonstrate digital plasmonic holography for direct in-plane imaging with propagating surface-plasmon waves. Imaging with surface plasmons suffers from the lack of simple in-plane lenses and mirrors. Lens-less digital holography techniques, however, rely on digitally decoding an interference pattern between a reference wave and an object wave. With far-field diffractive optics, this decoding scheme provides a full recording, i.e., a hologram, of the amplitude and phase of the object wave, giving three-dimensional information from a two-dimensional recording. For plasmonics, only a one-dimensional recording is needed, and both the phase and amplitude of the propagating plasmons can be extracted for high-resolution in-plane imaging. Here, we demonstrate lens-less, point-source digital plasmonic holography using two methods to record the plasmonic holograms: a dual-probe near-field scanning optical microscope and lithographically defined circular fluorescent screens. The point-source geometry gives in-plane magnification, allowing for high-resolution imaging with relatively lower-resolution microscope objectives. These results pave the way for a new form of in-plane plasmonic imaging, gathering the full complex wave, without the need for plasmonic mirrors or lenses.