Norihide Miyamura

Detection and correction of spectral and spatial misregistrations for hyperspectral data using phase correlation method.

Hyperspectral imaging sensors suffer from spectral and spatial misregistrations due to optical-system aberrations and misalignments. These artifacts distort spectral signatures that are specific to target objects and thus reduce classification accuracy. The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images. The Hyperion visible near-infrared subsystem is used as an example. An image registration method based on phase correlation demonstrates the accurate detection of the spectral and spatial misregistrations. Cubic spline interpolation using estimated properties makes it possible to modify the spectral signatures. The accuracy of the proposed postlaunch estimation of the Hyperion characteristics is comparable to that of the prelaunch measurements, which enables the accurate onboard calibration of hyperspectral sensors.

Detection and correction of spectral and spatial misregistrations for hyperspectral data

Hyperspectral imaging sensors suffer from spectral and spatial misregistrations. These artifacts prevent the accurate acquisition of the spectra and thus reduce classification accuracy. The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images. The Hyperion visible near-infrared (VNIR) subsystem is used as an example. An image registration method using normalized cross-correlation for characteristic lines in spectrum image demonstrates its effectiveness for detection of the spectral and spatial misregistrations. Cubic spline interpolation using estimated properties makes it possible to modify the spectral signatures. The accuracy of the proposed postlaunch estimation of the Hyperion properties has been proven to be comparable to that of the prelaunch measurements, which enables the precise onboard calibration of hyperspectral sensors.

Image based deformable mirror control for adaptive optics in satellite telescope

We are developing an adaptive optics system for earth observing remote sensing sensor. In this system, high spatial resolution has to be achieved by a lightweight sensor system due to the launcher’s requirements. Moreover, simple hardware architecture has to be selected to achieve high reliability. Image based AOS realize these requirements without wavefront sensor. In remote sensing, it is difficult to use a reference point source unless the satellite controls its attitude toward a star or it has a reference point source in itself. We propose the control algorithm of the deformable mirror on the basis of the extended scene instead of the point source. In our AOS, a cost function is defined using acquired images on the basis of the contrast in spatial or Fourier domain. The cost function is optimized varying the input signal of each actuator of the deformable mirror. In our system, the deformable mirror has 140 actuators. We use basis functions to reduce the number of the input parameters to realize real-time control. We constructed the AOS for laboratory test, and proved that the modulated wavefront by DM almost consists with the ideal one by directly measured using a Shack- Hartmann wavefront sensor as a reference.

Test results of optimal phase diversity selection using a LCOS-SLM for remote sensing adaptive optics

We propose an adaptive optics system using a Liquid crystal on Silicon Spatial Light Modulator (LCOS-SLM) for wavefront control. The phase diversity technique is used as a wavefront sensor, which estimates a wavefront aberration using processing images acquired by mission sensor instead of using additional wavefront sensor hardware. Because of simplicity in a hardware architecture, the phase diversity technique is suitable especially for a light weight remote sensing satellite. In the conventional phase diversity method, prior information, which is defined as a phase diversity, is applied to the optical system by defocusing. Then wavefront aberrations are estimated using the phase diversity and acquired images. For generating prior information, we uses the LCOS-SLM which generate arbitrary wavefront shape. In this cases, the selection of the phase diversity affect the estimation accuracy of the wavefront aberration. This paper describes the selection strategy of phase diversities, and then validates it by laboratory test.

Adaptive optics for small satellite remote sensing system using LCOS-SLM as a phase diversity generator

The purpose of this paper is to develop adaptive optics system which estimates degrading factors using observed images and automatically compensates the distorted wavefronts using a spatial light modulator (SLM). The system estimates optical wavefront aberrations by phase diversity method. The SLM which is used for wavefront compensation applies multiple time-series known wavefronts as a priori information to the optical system. By using the SLM for the phase diversity generator, it is possible to select the optimal number and shape of phase diversities for various kinds of natural modes of wavefront aberrations which are represented by the Zernike polynomials. In laboratory test, wavefront aberrations were generated by optical misalignments, and they were estimated as the coefficients of Zernike polynomials for an extended scene. The suggested method was validated by numerical simulations and laboratory tests. The high estimation accuracy of the distorted wavefront was demonstrated, and nearly diffraction limited images were acquired by wavefront compensation.

LARGE “FUROSHIKI” NET EXTENSION IN SPACE – SOUNDING ROCKET EXPERIMENT RESULTS

Abstract University of Tokyo and Kobe University conducted a sounding rocket experiment to deploy large “Furoshiki” net in space, which is a promising candidate for the future large antenna or solar power satellites. The experimental system consisting of mother and three daughter satellites as well as a folded net was separated from S-310 sounding rocket of JAXA/ISAS at the altitude of 110km, where the daughter satellites, after separated from mother satellite with 1.2 m/s velocity, deployed a large net of 14m-sized triangle. The deployment was quire successful without any tangling and the dynamics during deployment has been captured by cameras, INS and radar distance measurement system. Retro-directive antenna micro wave transmission experiment using 4 antennae on the bottom of satellites were conducted also successfully.

Similarity measure for spatial-spectral registration in hyperspectral era

In the hyperspectral era, the demand for data registration in spectral region is an important issue in addition to spatial region. Detection of smile and keystone phenomena that are caused by aberrations in spectrometer is related to registration activity, which is crucial for data fusion research. Hyperspectral Imager Suite (HISUI) is a next-generation Japanese optical sensor that is composed of a hyperspectral imager and a multispectral imager, which will be launched on Advanced Land Observation Satellite 3 (ALOS-3). Three similarity measures, normalized cross correlation (NCC), phase correlation (PC) and mutual information (MI), for spatial-spectral registration of hyperspectral data are discussed for Level-1 data processing of HISUI.

Laboratory test results for adaptive optics using image-based wavefront sensing for remote sensing

Large aperture optical system is required for high resolution and high signal to nose ratio remote sensing observations. In this case, adaptive optics is used to compensate the wavefront aberration generated by the misalignment or the thermal deformation of the optical elements. We use a liquid crystal on silicon spatial light modulator (LCOS-SLM) for the optical wavefront control, and image-based wavefront sensing which realize simple hardware architecture. For image-based sensing, a priori information is required in addition to the acquired images. We use phase diversity (PD) wavefront sensing method which applies a priori information called PD to the optics. By using PDs and acquired images, we can estimate arbitrary wavefront aberration. In this case, the sensitivity of the acquired image to the aberration mode depends on the applied PD. We use LCOS-SLM to apply the optimal set of PDs. We constructed adaptive optics system testbed using LCOS-SLM and USB camera. In this system, we used a Shack-Hartmann wavefront sensor (SHWS) to compare the estimated wavefront aberration with the actual wavefront measured by the SHWS. The laboratory test results show that the proposed system improves the optical performance of the remote sensing sensors.

Sub-pixel registration method for phase diversity wavefront sensor using spatial light modulator

The purpose of this paper is to develop sub-pixel registration method for adaptive optics system using phase diversity wavefront sensing with a spatial light modulator (SLM). The SLM which is used for wavefront compensation applies multiple time-series known wavefronts as a priori information to the optical system. By using the SLM for the phase diversity generator, it is possible to select the optimal number and shape of phase diversities for various kinds of natural modes of wavefront aberrations which are represented by the Zernike polynomials. In this case, a misregistration of several diversity images has to be compensated before using phase diversity algorithm. We extracted phase diversity method to estimate not only wavefront aberration but also parallel shift between images simultaneously. The suggested method was validated by numerical simulations, and the high estimation accuracy of the distorted wavefront was demonstrated, and nearly diffraction limited images were acquired by wavefront compensation by preventing noise due to misregistrations.

Onboard wavefront estimation using spatial light modulator as a phase diversity generator

We propose an adaptive optics system for a lightweight remote sensing sensor. The phase diversity (PD) technique, in which known wavefronts (Phase Diversity) are applied to the optics and the inherent aberrations are estimated using the acquired images without a priori information, is a key to realizing the system. For the reduction of computing cost and the enhancement of the estimation accuracy of aberration, a spatial light modulator (SLM) is adopted not only for wavefront compensator but also for PD generator. The SLM produces arbitrary “aberration modes” that are each represented by a Zernike polynomial. Therefore, optimal phase diversities are applied to the optical system and particular modes are effectively obtained, which makes it possible to overcome the conventional PD generated by defocusing that describes only quadratic form and lacks information of a particular mode. In order to solve the complex inverse problem of phase diversity with low computing cost, a general regression neural network (GRNN) is used. Moreover, principal component analysis compresses the input data for GRNN by extracting information from collected images in Fourier space, and reduces computation cost considerably. The performance is validated by numerical simulation, and the result of experiment using SLM is described.