A Variable Density Sampling Scheme for Compressive Fourier Transform Interferometry

نویسندگان

  • Amirafshar Moshtaghpour
  • Valerio Cambareri
  • Philippe Antoine
  • M. Roblin
  • Laurent Jacques
چکیده

Fourier Transform Interferometry (FTI) is an appealing Hyperspectral (HS) imaging modality in the applications demanding high spectral-resolution, such as fluorescence microscopy. However, the effective resolution of FTI is indeed limited due to the durability of biological elements when exposed to illuminating light; since over exposed biological elements suffer from photo-bleaching, i.e., a photochemical alteration. In this context, the acquisition of biological HS volumes based on Nyquist sampling rate of Optical Path Difference (OPD) axis leads to unpleasant trade-offs between spectral resolution, quality of HS volume, and light exposure intensity. In this paper we propose two variants of the FTI imager, i.e., Coded Illumination-FTI (CI-FTI) and Coded Aperture FTI (CA-FTI), based on the theory of compressed sensing, that efficiently modulate light exposure temporally (in CI-FTI) or spatiallytemporally (in CA-FTI). Leveraging a variable density sampling strategy we provide an optimum illumination and aperture coding, so that the light exposure imposed on a biological specimen is minimized while the spectral resolution is preserved. Our theoretical analysis consists in two parts, (i) the trade-off between exposure intensity and the quality of acquired HS volume for a fixed spectral resolution; (ii) the best HS volume quality for a fixed spectral resolution and constrained exposure intensity budget. Our contributions can be adapted to an FTI imager without hardware modification. The reconstruction of HS volumes from compressive sensing FTI measurements relies on an `1-norm minimization problem promoting 3D HS sparsity prior. Numerically, we support the proposed methods on synthetic data and simulated compressed sensing measurements (from actual FTI measurements) under various scenarios. In particular, the HS volume of biological samples that are linearly mixed with fluorochrome spectral signatures can be reconstructed with a 3-10 fold reduction of exposure.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy

Fourier Transform Interferometry (FTI) is an interferometric procedure for acquiring HyperSpectral (HS) data. Recently, it has been observed that the light source highlighting a (biologic) sample can be coded before the FTI acquisition in a procedure called Coded Illumination-FTI (CI-FTI). This turns HS data reconstruction into a Compressive Sensing (CS) problem regularized by the sparsity of t...

متن کامل

Efficient modal analysis using compressive optical interferometry.

Interferometry is routinely used for spectral or modal analysis of optical signals. By posing interferometric modal analysis as a sparse recovery problem, we show that compressive sampling helps exploit the sparsity of typical optical signals in modal space and reduces the number of required measurements. Instead of collecting evenly spaced interferometric samples at the Nyquist rate followed b...

متن کامل

Beyond incoherence: stable and robust sampling strategies for compressive imaging

In many signal processing applications, one wishes to acquire images that are sparse in transform domains such as spatial finite differences or wavelets using frequency domain samples. For such applications, overwhelming empirical evidence suggests that superior image reconstruction can be obtained through variable density sampling strategies that concentrate on lower frequencies. The wavelet a...

متن کامل

Compressed Wideband Spectrum Sensing Based on Discrete Cosine Transform

Discrete cosine transform (DCT) is a special type of transform which is widely used for compression of speech and image. However, its use for spectrum sensing has not yet received widespread attention. This paper aims to alleviate the sampling requirements of wideband spectrum sensing by utilizing the compressive sampling (CS) principle and exploiting the unique sparsity structure in the DCT do...

متن کامل

Compressive Sensing-based Mrireconstruction in Fractional Fourier Domain

Compressive sensing is an emerging field in digital signal processing. It introduce a new technique to image reconstruction from less amount of data. This methodology reduces imaging time in MRI. Compressive sensing exploit the sparsity of the signal. In this paper Fractional Fourier is used as sparsifying transform and signal sampled by random sampling . Run length encoding is applied to code ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1801.10432  شماره 

صفحات  -

تاریخ انتشار 2018