Lithographic source optimization based on adaptive projection compressive sensing
نویسندگان
چکیده
منابع مشابه
Block-Based Compressive Sensing Using Soft Thresholding of Adaptive Transform Coefficients
Compressive sampling (CS) is a new technique for simultaneous sampling and compression of signals in which the sampling rate can be very small under certain conditions. Due to the limited number of samples, image reconstruction based on CS samples is a challenging task. Most of the existing CS image reconstruction methods have a high computational complexity as they are applied on the entire im...
متن کاملOptimized Projection Matrix for Compressive Sensing
Compressive sensing (CS) is mainly concerned with low-coherence pairs, since the number of samples needed to recover the signal is proportional to the mutual coherence between projection matrix and sparsifying matrix. Until now, papers on CS always assume the projection matrix to be a random matrix. In this paper, aiming at minimizing the mutual coherence, a method is proposed to optimize the p...
متن کاملInterferometric ISAR Imaging Based on Compressive Sensing
Inverse Synthetic Aperture Radar (ISAR) images are often used for target classification and recognition applications. However, conventional 2D images do not provide the height information about the scattering centers. In this paper, an interferometric ISAR imaging method based on compressive sensing (CS) is proposed that is able to estimate the scatterering centres heights. The interferometric ...
متن کاملBayesian Compressive Sensing Based on Importance Models
To solve the problem that all row signals use the same reconstruction algorithm, a type of Bayesian compressive sensing based on importance models is proposed, which reconstructs more important signals firstly even if losing some unimportant signals. Compared to Bayesian compressive sensing whose performances is not well when sampling ratio is lower, the proposed algorithms can improve reconstr...
متن کاملWaveform Optimization for Compressive Sensing Radar Systems
Compressive sensing (CS) provides a new paradigm in data acquisition and signal processing for radar. In this work, we investigate the performance of several deterministic waveforms for the basic problem of range-only estimation in CS-radar system. We investigate the effects of a digital RF system from signal generation at the transmitter, to sparse signal recovery at the receiver, on the incoh...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Optics Express
سال: 2017
ISSN: 1094-4087
DOI: 10.1364/oe.25.007131