Detecting landscape forms using Fourier transformation and singular value decomposition (SVD)
نویسندگان
چکیده
Landscape structure is a main determinant of ecological landscape potentials. The basic differentiation of relief into depressions and elevations at deliberately chosen scales can be managed comfortably by the Fourier transformation. The automated extraction of these structures from an elevation map using Fourier transformation or singular value decomposition can help to overcome complicated and errorprone procedures based on the determination of numerical structure parameters such as slope and aspect. The combination of automated extraction methods and moving window technology can lead to further, more integrated insights related to complex landscape patterns. & 2009 Elsevier Ltd. All rights reserved.
منابع مشابه
Disguised Face Recognition by Using Local Phase Quantization and Singular Value Decomposition
Disguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is presented which deals with two main challenges. The first challenge is when an individual intentionally alters the appearance ...
متن کاملFeature Extraction of Visual Evoked Potentials Using Wavelet Transform and Singular Value Decomposition
Introduction: Brain visual evoked potential (VEP) signals are commonly known to be accompanied by high levels of background noise typically from the spontaneous background brain activity of electroencephalography (EEG) signals. Material and Methods: A model based on dyadic filter bank, discrete wavelet transform (DWT), and singular value decomposition (SVD) was developed to analyze the raw data...
متن کاملGraph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members
Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...
متن کاملSingular Value Decomposition based Steganography Technique for JPEG2000 Compressed Images
In this paper, a steganography technique for JPEG2000 compressed images using singular value decomposition in wavelet transform domain is proposed. In this technique, DWT is applied on the cover image to get wavelet coefficients and SVD is applied on these wavelet coefficients to get the singular values. Then secret data is embedded into these singular values using scaling factor. Different com...
متن کاملSingular Value Decomposition in Image Noise Filtering and Reconstruction
The Singular Value Decomposition (SVD) has many applications in image processing. The SVD can be used to restore a corrupted image by separating significant information from the noise in the image data set. This thesis outlines broad applications that address current problems in digital image processing. In conjunction with SVD filtering, image compression using the SVD is discussed, including ...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Computers & Geosciences
دوره 35 شماره
صفحات -
تاریخ انتشار 2009