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1910 Ultra High Compression for Weather Radar Reflectivity Data Storage and TransmissionPravas R. Mahapatra, Indian Institute of Science, Bangalore, Karnataka, India; and V. V. MakkapatiIntroduction The highly limited bandwidth (and high cost of bandwidth when available) of ground-aircraft and aircraft-ground data links necessitates maximal compression of radar-generated weather pictures for transmission to and from aircraft. Compression of pictorial data is a subject of much research. However, general-purpose picture compression algorithms seldom achieve compression ratios better than an order of magnitude. Specific compression schemes optimized for weather data hold the promise of higher degrees of compression. One such class of schemes is based on contour representation of weather fields. The contours may be represented by, e.g., elliptical or polygonal segments, each represented by a few parameters which may be transmitted over the data link for reconstruction of the contours at the receiving end. This paper reports a novel method of compressing generalized weather radar reflectivity contours by a limited number of control points, and retrieving the contours using spline interpolation. We have achieved compression ratios exceeding a hundred while preserving the meteorologically significant features in the data field. The results are compared with other available methods in terms of compression factor and fidelity of reproduction. Contour Tracing The 2-D reflectivity distribution is converted into a binary image by applying a threshold. Any threshold may be applied, but it is more meaningful to choose one of the six threshold values specified by the National Weather Service (NWS) corresponding to different levels of severe weather phenomena. The boundary separating an area of 0's from an area of 1's is called a contour. Contours enclosing a zone of 1's are called 'region contours', and boundaries within these region contours which enclose only 0's are called 'holes'. It is possible for region contours and holes to be nested, i.e. there may be region contours within holes, and so on. We use the radial sweep algorithm to trace the contours. However, this algorithm does not automatically trace internal structures of contours such as holes, region contours inside them, and nested contours. Further, it traces only one contour at a time, only after the contour has been initiated through a search procedure. We overcome these limitations by using the Pavlidis' scheme, applying it recursively to trace nested holes and region contours. Extracting Control Points Typical reflectivity contours present a rather zig-zag appearance. The aim is to capture the shape of the curve faithfully with a limited number of significant points. A novel scheme for extracting these control points is proposed in this paper. We first average the given contour over a sliding segment to obtain a smoothed curve. The deviation of each point on the original contour from the nearest point on the smoothed curve is calculated. From this data, the points of crossing between the original contour and the smoothed curve are determined and stored. Points with maximum deviation lying between two consecutive crossings are taken as control points. If the distance between two adjacent crossings is large (greater than a threshold), additional control points are introduced by bisecting the arcs (of original contour) between the control point and the crossings on both sides. This scheme works in most situations, but may not extract proper control points for smooth contours and small contours (e.g. contours with Figure 1: Original PPI image Contour Transmission and Reconstruction The thresholds used for encoding are stored in a look-up table, and only the indices need to be transmitted to minimize bit requirements. The closed contours for any given threshold are numbered. Further, a tag bit of 0 and 1 is used to distinguish region and hole contours respectively. The control points for each numbered contour are transmitted in terms of their coordinates, referenced relative to the contour?s minimum bounding rectangle for minimizing bit requirements. At the receiving end, the contours are retrieved using the B-spline fit on the control points, employing a special technique to handle closed curves. A boundary fill algorithm is used to fill the interior of each region contour (identified by its tag bit), excluding any embedded holes, with the color corresponding to its threshold value. Superposition of filled contours of all valid threshold levels would display the total reflectivity picture to the pilot. Figure 2: A raw contour (gray line) obtained by 30-dB thresholding, and its smoothed version (black line). Control points are shown as small black squares. Performance Evaluation The performance of the compression scheme is evaluated by the compression ratio it provides and contour reproduction fidelity. We have derived an expression for the bit requirements for the compressed image in terms of the number of control points, contour sizes, and other secondary parameters. Based on this the compression ratio can be evaluated. The compression algorithm has been tested using WSR-88D radar reflectivity Level II data (512 x 512 pixels). NOAA standard color table ('legend') is used for displaying the reflectivity, with the background (originally black) changed to white (Fig. 1). The largest-area contour appearing in the 30-dB-threshold section of the picture is shown in Fig. 2 in raw form and after smoothing it over 10% of the contour length. Root Mean Square Error (RMSE) obtained for this contour using the methods of Gertz and Grappel (US patent 5363107) and Burdon (Patent 6614425) are 1.1348 and 1.2104 respectively, while our scheme has resulted in 1.1197 when 66 control points are transmitted, yielding a compression ratio of 112. This level of compression is very high compared with any of the general-purpose image compression schemes. The reconstructed image (Fig. 3) is found to retain all of the meteorologically significant features of the original image. Further, the computational time even on a medium-speed (1.8. MHz) Pentium PC remains within a few percent of typical radar scan periods, permitting real-time compression and reconstruction of the images. Figure 3: Reconstructed PPI image

Highly compressed mid-infrared optical waves in a thin dielectric crystal on monocrystalline gold substrate investigated for the first time using a high-resolution scattering-type scanning near-field optical microscope.

KAIST researchers and their collaborators at home and abroad have successfully demonstrated a new platform for guiding the compressed light waves in very thin van der Waals crystals. Their method to guide the mid-infrared light with minimal loss will provide a breakthrough for the practical applications of ultra-thin dielectric crystals in next-generation optoelectronic devices based on strong light-matter interactions at the nanoscale.

Challenged by these limitations, four research groups combined their efforts to develop a unique experimental platform using advanced fabrication and measurement methods. Their findings were published in Science Advances on July 13.

A KAIST research team led by Professor Min Seok Jang from the School of Electrical Engineering used a highly sensitive scanning near-field optical microscope (SNOM) to directly measure the optical fields of the hyperbolic image phonon-polaritons (HIP) propagating in a 63 nm-thick slab of hexagonal boron nitride (h-BN) on a monocrystalline gold substrate, showing the mid-infrared light waves in dielectric crystal compressed by a hundred times.

Professor Jang and a research professor in his group, Sergey Menabde, successfully obtained direct images of HIP waves propagating for many wavelengths, and detected a signal from the ultra-compressed high-order HIP in a regular h-BN crystals for the first time. They showed that the phonon-polaritons in van der Waals crystals can be significantly more compressed without sacrificing their lifetime.

This became possible due to the atomically-smooth surfaces of the home-grown gold crystals used as a substrate for the h-BN. Practically zero surface scattering and extremely small ohmic loss in gold at mid-infrared frequencies provide a low-loss environment for the HIP propagation. The HIP mode probed by the researchers was 2.4 times more compressed and yet exhibited a similar lifetime compared to the phonon-polaritons with a low-loss dielectric substrate, resulting in a twice higher figure of merit in terms of the normalized propagation length.

The ultra-smooth monocrystalline gold flakes used in the experiment were chemically grown by the team of Professor N. Asger Mortensen from the Center for Nano Optics at the University of Southern Denmark.

Mid-infrared spectrum is particularly important for sensing applications since many important organic molecules have absorption lines in the mid-infrared. However, a large number of molecules is required by the conventional detection methods for successful operation, whereas the ultra-compressed phonon-polariton fields can provide strong light-matter interactions at the microscopic level, thus significantly improving the detection limit down to a single molecule. The long lifetime of the HIP on monocrystalline gold will further improve the detection performance.

Furthermore, the study conducted by Professor Jang and the team demonstrated the striking similarity between the HIP and the image graphene plasmons. Both image modes possess significantly more confined electromagnetic field, yet their lifetime remains unaffected by the shorter polariton wavelength. This observation provides a broader perspective on image polaritons in general, and highlights their superiority in terms of the nanolight waveguiding compared to the conventional low-dimensional polaritons in van der Waals crystals on a dielectric substrate.

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