Image quality of increased along-scan sampling for remote sensing systems

Fiete, Robert D.; Tantalo, Theodore A.

doi:10.1117/1.602053

Cited by 35 publications

(26 citation statements)

References 2 publications

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“…The image quality of the satellite images can be expressed by many technical parameters, such as the GSD, the modulation transfer function (MTF) and the signal-to-noise ratio (SNR) [3][4][5]. However, these parameters cannot completely describe the quality of the image [6], and they are used primarily in technical fields and by technical people, such as satellite designers, satellite manufacturers, optical engineers or electric engineers; as a result, the parameters provide quality information and feedback for these technical workers.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

Li¹,

Luo²,

Zhu³

2014

Remote Sensing

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Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3 (Ziyuan-3) satellite is the first civil high resolution mapping satellite in China, which was established in 2012. So far, there has been no reports on adopting NIIRS as the common indicator for the quality assessment of that satellite image data. This lack of a common quality indicator results in a gap between satellite data users around the world and those in China regarding the understanding of the quality and usability of ZY-3 data. To overcome the gap, using the general image-quality equation (GIQE), this study evaluates the ZY-3 sensor-corrected (SC) panchromatic nadir (NAD) data in terms of the NIIRS. In order to solve the uncertainty resulting from the exceeding of the ground sample distance (GSD) of ZY-3 data (2.1 m) in GIQE (less than 2.03 m), eight images are used to establish the relationship between the manually obtained NIIRS and the GIQE predicted NIIRS. An adjusted GIQE is based on the relationship and verified by another five images. Our study demonstrates that the method of using adjusted GIQE for calculating NIIRS can be used for the quality assessment of ZY-3 satellite images and reveals that the NIIRS value of ZY-3 SC NAD data is about 2.79.

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Section: Introductionmentioning

confidence: 99%

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

Li¹,

Luo²,

Zhu³

2014

Remote Sensing

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“…A delta-NIIRS of 0.1 is considered to be just perceptible. 10 Hence a delta-element, being worth 0.167 delta-NIIRS, would be significantly greater than (1.67 times) just discernible. Table 1 shows the relationship among delta-groups, delta-elements, delta-NIIRS, and ratios of effective resolution.…”

Section: Six-aperture Simulationsmentioning

confidence: 99%

Direct-detection synthetic-aperture coherent imaging by phase retrieval

Fienup

2017

Opt. Eng

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Abstract. This paper describes a way to synthesize a larger coherent aperture from smaller apertures combined with motion, when only intensities are measured. It relies on collecting intensity patterns in two planes for each aperture, for example, the aperture plane and an image plane, and using a phase-retrieval algorithm to reconstruct the optical field in the aperture plane. As the sensor moves forward, a larger two-dimensional aperture is synthesized, allowing a much finer resolution image to be reconstructed. An algorithm to correct for the relative pointing (tip and tilt phases) and piston errors between different apertures and at different times is needed to phase up the synthetic aperture. Results of simulations, including the effects of speckle, are shown, and practical considerations are evaluated. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10.1117/1.OE. 56.11.113111] Keywords: synthetic aperture; imaging; phase retrieval; phase-error correction; image reconstruction; heterodyne.Paper 171359 received Aug. 28, 2017; accepted for publication Nov. 1, 2017; published online Nov. 21, 2017. IntroductionTo achieve fine resolution imagery at a given long distance and in a given wavelength band, one needs a collection system (telescopes) having a large enough effective aperture. As an alternative to building and deploying larger single-aperture systems (which become increasingly bulky, heavy, and costly), one can perform aperture synthesis. This can be done either passively (using reflected sunlight) as in Michelson stellar interferometry or actively as in coherent laser illumination with phase-sensitive detection. Michelson interferometry requires two or more simultaneous apertures having substantial motion of one aperture relative to another and, for a variety of reasons, is poorly suited to looking downward at the earth. One could use laser synthetic-aperture radar (SAR) in which temporal or chirped frequency sensing provides range information and forward motion provides alongtrack resolution; temporal heterodyne sensing over large temporal bandwidths is required for fine range resolution. Digital holography, also known as spatial heterodyne, can achieve fine resolution in angle-angle space by a string of apertures in the cross-track direction combined with aperture synthesis in the along-track direction; it can employ narrow laser bandwidths but must still interfere the return field from the object with a local oscillator (LO), requiring stable LO distribution from a master laser to all the telescopes. One could employ multiple small apertures underneath the wings of an aircraft, or on a group of small satellites, or on a moving ground vehicle, to synthesize a large two-dimensional (2-D) aperture with fine resolution. Images from laser illumination systems exhibit speckle that degrades the effective resolution unless...

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“…Additionally, grayscale cameras will typically balance sampling with other factors, such as signal-to-noise ratio (SNR). This generally results in undersampled, aliased images [6]. Because CFA cameras trade spatial sampling for color information, aliasing issues are exacerbated.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, we expect that c 1,9 (p) will have less interpolation error than c 1,6 (p). The weights will exploit this information by means of Equation (6).…”

Section: Interpolation Error Weightmentioning

confidence: 99%

Robust super-resolution by fusion of interpolated frames for color and grayscale images

Karch

Hardie

2015

Front. Phys.

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Multi-frame super-resolution (SR) processing seeks to overcome undersampling issues that can lead to undesirable aliasing artifacts in imaging systems. A key factor in effective multi-frame SR is accurate subpixel inter-frame registration. Accurate registration is more difficult when frame-to-frame motion does not contain simple global translation and includes locally moving scene objects. SR processing is further complicated when the camera captures full color by using a Bayer color filter array (CFA). Various aspects of these SR challenges have been previously investigated. Fast SR algorithms tend to have difficulty accommodating complex motion and CFA sensors. Furthermore, methods that can tolerate these complexities tend to be iterative in nature and may not be amenable to real-time processing. In this paper, we present a new fast approach for performing SR in the presence of these challenging imaging conditions. We refer to the new approach as Fusion of Interpolated Frames (FIF) SR. The FIF SR method decouples the demosaicing, interpolation, and restoration steps to simplify the algorithm. Frames are first individually demosaiced and interpolated to the desired resolution. Next, FIF uses a novel weighted sum of the interpolated frames to fuse them into an improved resolution estimate. Finally, restoration is applied to improve any degrading camera effects. The proposed FIF approach has a lower computational complexity than many iterative methods, making it a candidate for real-time implementation. We provide a detailed description of the FIF SR method and show experimental results using synthetic and real datasets in both constrained and complex imaging scenarios. Experiments include airborne grayscale imagery and Bayer CFA image sets with affine background motion plus local motion.

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Image quality of increased along-scan sampling for remote sensing systems

Cited by 35 publications

References 2 publications

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

Direct-detection synthetic-aperture coherent imaging by phase retrieval

Robust super-resolution by fusion of interpolated frames for color and grayscale images

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