Denoising is significant in many fields, especially for computational imaging. Coherent diffraction imaging and speckle correlation imaging are regarded as the most promising computational imaging techniques. The above two imaging techniques can be classified as phase-retrieval-based imaging due to the phase-retrieval is a vital procedure for object reconstruction. However, the acquisition process would generate unavoidable noise and participate in the iteration process of phase-retrieval. Hence, it is necessary to denoising after obtained the original reconstruction image. Here, a denoising method that based on connected domain is proposed for phase-retrieval method. We experimentally demonstrate the denoising results and quantitatively analyze the effect. Comparison of the classical median filter, wiener filter and bilateral filter, our method shows a satisfactory denoising effect. Our results prove that connected domain denoising is useful and promising, which provides a new post-processing denoising method for phase-retrieval-based imaging.
Imaging objects hidden behind opaque layers is significant in many fields, with applications ranging from biomedical imaging to defense security. Techniques based on memory-effect scattering imaging have been developed in the past decade. The existing memory-effect-based scattering imaging techniques can be divided into two categories based on the working principle of light sources. In these methods, phase-retrieval algorithm is used to reconstruct object from the power spectrum diffraction patterns as the last step. Although both of them achieve single-shot scattering imaging, the experimental set-up is quite different. It is noted that the coherent diffraction imaging is introduced to the scattering imaging field using the visible coherent light. The principle and setup of the aforementioned two methods are analyzed and summarized respectively. We experimentally demonstrate the reconstruction and evaluate the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Image Measurement (SSIM). As these technologies are limited to short range and memory effect range, the potential to imaging with wide field of view and long distance requires further exploration.
The mutual interference method is introduced to detect vortex beams. For the coaxial interference between l1-order and l2-order vortex beams, the intensity distribution is spirally fan-shaped. The partition number N=|l2-l1|, and the spiral direction can distinguish the sign of topological charge with larger absolute value between |l1| and |l2|. Fork-shaped fringes appear in the center for the small-angle interference between vortex beams with incident angle β1 and β2. The forking number between two fringes agrees with N=|l2-l1|, and the forks face upward when l1<l2 & β1<β2, or l1<l2 & β1<β2, and face downward when l1<l2 & β1<β2, or l1<l2 & β1<β2. Especially, when one of the beams is a Gaussian beam, such as l1=0, the value and sign of the topological charge l2 of the other vortex beam can be simply detected. The mutual interference method can conveniently detect the value and sign of vortex beams without borrowing redundant devices.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.