Mathematical optimization versus practical performance: A case study based on the maximum entropy criterion in image reconstruction

1982 ◽  
pp. 96-112 ◽  
Author(s):  
Gabor T. Herman
Keyword(s):  
Image Reconstruction ◽  
Maximum Entropy ◽  
Mathematical Optimization ◽  
Practical Performance ◽  
Entropy Criterion

Most likely maximum entropy for population analysis: A case study in decompression sickness prevention

2015 ◽  
Author(s):  
Youssef Bennani ◽  
Luc Pronzato ◽  
Maria João Rendas
Keyword(s):  
Maximum Entropy ◽  
Decompression Sickness ◽  
Population Analysis

Maximum Entropy Image Reconstruction in Eddy Current Tomography

1993 ◽  
pp. 273-278
Author(s):  
Mila Nikolova ◽  
Ali Mohammad-Djafari
Keyword(s):  
Image Reconstruction ◽  
Maximum Entropy ◽  
Eddy Current

Bayesian Maximum Entropy Image Reconstruction from the Scattered Field Data

1993 ◽  
pp. 265-272
Author(s):  
Maï Khuong Nguyen ◽  
Ali Mohammad-Djafari
Keyword(s):  
Image Reconstruction ◽  
Maximum Entropy ◽  
Scattered Field ◽  
Field Data ◽  
Bayesian Maximum Entropy

scholarly journals Deep Learning in Hyperspectral Image Reconstruction from Single RGB images—A Case Study on Tomato Quality Parameters

2020 ◽  
Vol 12 (19) ◽  
pp. 3258
Author(s):  
Jiangsan Zhao ◽  
Dmitry Kechasov ◽  
Boris Rewald ◽  
Gernot Bodner ◽  
Michel Verheul ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Hyperspectral Image ◽  
Absolute Error ◽  
Solid Content ◽  
Image Resolution ◽  
Soluble Solid Content ◽  
Quality Properties ◽  
Tomato Quality ◽  
Rgb Images

Hyperspectral imaging has many applications. However, the high device costs and low hyperspectral image resolution are major obstacles limiting its wider application in agriculture and other fields. Hyperspectral image reconstruction from a single RGB image fully addresses these two problems. The robust HSCNN-R model with mean relative absolute error loss function and evaluated by the Mean Relative Absolute Error metric was selected through permutation tests from models with combinations of loss functions and evaluation metrics, using tomato as a case study. Hyperspectral images were subsequently reconstructed from single tomato RGB images taken by a smartphone camera. The reconstructed images were used to predict tomato quality properties such as the ratio of soluble solid content to total titratable acidity and normalized anthocyanin index. Both predicted parameters showed very good agreement with corresponding “ground truth” values and high significance in an F test. This study showed the suitability of hyperspectral image reconstruction from single RGB images for fruit quality control purposes, underpinning the potential of the technology—recovering hyperspectral properties in high resolution—for real-world, real time monitoring applications in agriculture any beyond.

A new approach to the solution of the maximum entropy image reconstruction problem

2005 ◽  
Author(s):  
Xinhua Zhuang ◽  
Kai-Bor Yu ◽  
R. Haralick
Keyword(s):  
Image Reconstruction ◽  
Maximum Entropy ◽  
Reconstruction Problem ◽  
New Approach
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