Efficient encoding and rapid decoding for interactive visualization of large three-dimensional hyperspectral chemical images.

نویسندگان

  • Stephen E Reichenbach
  • Alex Henderson
  • Robert Lindquist
  • Qingping Tao
چکیده

Interactive visualization of data from a new generation of chemical imaging systems requires coding that is efficient and accessible. New technologies for secondary ion mass spectrometry (SIMS) generate large three-dimensional, hyperspectral datasets with high spatial and spectral resolution. Interactive visualization is important for chemical analysis, but the raw dataset size exceeds the memory capacities of typical current computer systems and is a significant obstacle. This paper reports the development of a lossless coding method that is memory efficient, enabling large SIMS datasets to be held in fast memory, and supports quick access for interactive visualization. The approach provides pixel indexing, as required for chemical imaging applications, and is based on the statistical characteristics of the data. The method uses differential time-of-flight to effect mass-spectral run-length-encoding and uses a scheme for variable-length, byte-unit representations for both mass-spectral time-of-flight and intensity values. Experiments demonstrate high compression rates and fast access.

برای دانلود رایگان 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

Visualization and analysis of large three-dimensional hyperspectral images

New technologies for Secondary Ion Mass Spectrometry (SIMS) produce three-dimensional hyperspectral chemical images with high spatial resolution and fine mass-spectral precision. SIMS imaging of biological tissues and cells promises to provide an informational basis for important advances in a wide variety of applications, including cancer treatments. However, the volume and complexity of data ...

متن کامل

Three-Dimensional Wavelet-Based Compression of Hyperspectral Images

Hyperspectral images may be treated as a three-dimensional data set for the purposes of compression. Here we present some compression techniques based on a three-dimensional wavelet transform that produce compressed bit streams with many useful properties. These properties are progressive quality encoding and decoding, progressive lossyto-lossless encoding, and progressive resolution decoding. ...

متن کامل

کاهش ابعاد داده‌های ابرطیفی به منظور افزایش جدایی‌پذیری کلاس‌ها و حفظ ساختار داده

Hyperspectral imaging with gathering hundreds spectral bands from the surface of the Earth allows us to separate materials with similar spectrum. Hyperspectral images can be used in many applications such as land chemical and physical parameter estimation, classification, target detection, unmixing, and so on. Among these applications, classification is especially interested. A hyperspectral im...

متن کامل

Improvement of the Classification of Hyperspectral images by Applying a Novel Method for Estimating Reference Reflectance Spectra

Hyperspectral image containing high spectral information has a large number of narrow spectral bands over a continuous spectral range. This allows the identification and recognition of materials and objects based on the comparison of the spectral reflectance of each of them in different wavelengths. Hence, hyperspectral image in the generation of land cover maps can be very efficient. In the hy...

متن کامل

Overlap-based feature weighting: The feature extraction of Hyperspectral remote sensing imagery

Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. We propose to use overlap-based feature weigh...

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

عنوان ژورنال:
  • Rapid communications in mass spectrometry : RCM

دوره 23 9  شماره 

صفحات  -

تاریخ انتشار 2009