Results 211 to 220 of about 102,502 (260)

Mixed pixel classification with robust statistics

IEEE Transactions on Geoscience and Remote Sensing, 1997
The authors present a novel method for mixed pixel classification where the Hough transform and the trimmed means methods are used to classify small sets of pixels. They compare the performance of these methods with the least squares error method, and they show that in the presence of outliers, the trimmed means method is far more reliable than the ...
Panagiota Bosdogianni, Maria Petrou, Josef Kittler   +2 more
exaly   +2 more sources

A Maximum Entropy Approach to Unsupervised Mixed-Pixel Decomposition

IEEE Transactions on Image Processing, 2007
Due to the wide existence of mixed pixels, the derivation of constituent components (endmembers) and their fractional proportions (abundances) at the subpixel scale has been given a lot of attention. The entire process is often referred to as mixed-pixel decomposition or spectral unmixing.
Lidan Miao, Hairong Qi, Harold Szu
exaly   +3 more sources

Calculation of clumping index of mixed pixel and scale analysis

2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
Clumping index is an important vegetation structure parameter to describe the foliage clumping in canopy quantitatively. It is defined as the ratio of the effective leaf area index to the true leaf area index. In previous studies, it is generally considerate that cluster of canopy and below canopy scale in pure pixel.
Qingmiao Ma, Qinhuo Liu
exaly   +2 more sources

Artificial intelligence for mixed pixel resolution

2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
Mixed pixels are usually the biggest reason for lowered success in classification accuracy. Aiming at the characteristics of remote sensing image classification, the mixed pixel problem is one of the main factors that affect the improvement of classification precision in image.
Nitish Gupta, V. K. Panchal
openaire   +1 more source

To separate mixed pixel temperature using differential coefficient of pixel mixed temperature to vegetation fractional cover

Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05., 2005
This Two-layer surface fluxes model is suitable to inhomogenous soil-vegetation surface. The key step is to separate mixed pixel surface temperature. ATSR's sensor can provide two view angles for separating the temperature. However, the areas are different between the pixel at nadir view and the pixel at forward view, which would result in some errors.
Renhua Zhang, Xiaomin Sun 0002, Zhao-Liang Li, Jin-Ping Xu, Jing Tian, Zhilin Zhu, Weimin Wang 0005   +6 more
openaire   +1 more source

Illumination invariant unmixing of sets of mixed pixels

IEEE Transactions on Geoscience and Remote Sensing, 2001
The authors propose some statistics of distributions of sets of pixels corresponding to rough surfaces, which are illumination invariant and therefore they can characterize the distributions irrespective of the solar angle. The illumination invariant statistics are used to solve the linear spectral unmixing problem for sets of mixed pixels, taking into
Maria Faraklioti, Maria Petrou
openaire   +1 more source

Mixed pixel classification with the randomized Hough transform

Proceedings of 13th International Conference on Pattern Recognition, 1996
We propose the use of the randomized Hough transform algorithm for the determination of the proportions of pure classes present in sets of mixed pixels, for large datasets (for which the deterministic Hough is prohibitively slow) and in the presence of outliers (i.e. in cases that the classical least square error method cannot cope). We demonstrate our
Heikki Kälviäinen, Panagiota Bosdogianni, Maria Petrou, Josef Kittler   +3 more
openaire   +1 more source