Noise removal is a fundamental problem in image processing. Among many approaches, total variation (TV) has attracted great attention because of its advantage in preserving edges. However, it tends to exhibit some undesired staircase artifacts. Fractional-order TV (FTV) can overcome the drawback mentioned above, yet it does not take enough neighborhood information into account. An extension of FTV, four-directional FTV (FTV4) is put forward to explore more directional information of an image. We solve this FTV4 model by adopting the split Bregman algorithm and fast Fourier transform theory. An accelerated step is added in the algorithm to make it converge faster. To decrease the computation time, we introduce the convolution theory and calculate the matrix difference in the frequency domain instead of space domain. Experimental results show that the proposed image denoising model performs better than other state-of-the-art models in most cases.
The high computational complexity of tree-based multipath search approaches makes putting them into practical use difficult. However, reselection of candidate atoms could make the search path more accurate and efficient. We propose a multipath greedy approach called fast sparsity adaptive multipath matching pursuit (fast SAMMP), which performs a sparsity adaptive tree search to find the sparsest solution with better performances. Each tree branch acquires K atoms, and fast SAMMP reselects the best K atoms among 2K atoms. Fast SAMMP adopts sparsity adaptive techniques that allow more practical applications for the algorithm. We demonstrated the reconstruction performances of the proposed fast scheme on both synthetically generated one-dimensional signals and two-dimensional images using Gaussian observation matrices. The experimental results indicate that fast SAMMP achieves less reconstruction time and a much higher exact recovery ratio compared with conventional algorithms.
X wave has a large depth of field and may have important application in ultrasonic imaging to provide high frame rate (HFR). However, the HFR system suffers from lower spatial resolution. In this paper, a study of nonlinear imaging with X wave is presented to improve the resolution. A theoretical description of realizable nonlinear X wave is reported. The nonlinear field is simulated by solving the KZK nonlinear wave equation with a time-domain difference method. The
results show that the second harmonic field of X wave has narrower mainlobe and lower sidelobes than the fundamental field. In order to evaluate the imaging effect with X wave, an imaging model involving numerical calculation of the KZK equation, Rayleigh-Sommerfeld integral, band-pass filtering and envelope detection is constructed to obtain 2D fundamental and second harmonic images of scatters in tissue-like medium. The results indicate that if X wave is used,
the harmonic image has higher spatial resolution throughout the entire imaging region than the fundamental image, but higher sidelobes occur as compared to conventional focus imaging. A HFR imaging method with higher spatial resolution is thus feasible provided an apodization method is used to suppress sidelobes.
The design and fabrication of a Monothically integrated dual-wavelength tunable photodetector are reported.
The dual-wavelength character is realized by introducing a taper substrate. The photodetector operating on
long wavelength is Monothically integrated by using heteroepitaxy growth of InP-In0.53Ga0.47As-InP p-i-n
structure on GaAs based GaAs/AlAs Fabry-Perot filter structure, which can be tuned by thermal-optic effect.
High quality heteroepitaxy was realized by employing a thin low-temperature buffer layer. The integrated
device with a dual-peak distance of 7nm (1530nm,1537nm) , a wavelength tuning range of 5.0 nm, and a
3-dB bandwidth of 5.9 GHz was demonstrated, according with the theoretical simulation.
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.