Remote Sensing Image Sharpening by Integrating Multispectral Image Super-Resolution and Convolutional Sparse Representation Fusion

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Single-image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visu...

متن کامل

Simultaneous image fusion and super-resolution using sparse representation

1566-2535/$ see front matter 2012 Elsevier B.V. A doi:10.1016/j.inffus.2012.01.008 ⇑ Corresponding author. Tel.: +86 731 88822924. E-mail addresses: [email protected] (H. Yin), sh [email protected] (L. Fang). Given multiple source images of the same scene, image fusion integrates the inherent complementary information into one single image, and thus provides a more complete and accurate de...

متن کامل

Multispectral image data fusion using POCS and super-resolution

The problem of image data fusion coming from different sensors imaging the same object is to try to obtain a result that integrates the best characteristics of each one of those sensors. In this work, we want to combine the characteristics of multispectral (better spectral definition) and panchromatic (better space definition) images, using the bands from the satellites Landsat-7 (panchromatic)...

متن کامل

Single Image Super Resolution Using Sparse Representation with Image Fusion Principle

A suggested single image super resolution algorithm is proposed based on image fusion principle. Magnetic resonance and computed tomography images are interpolated using two algorithms that use sparse-representation modeling with dictionary learning. The MR and CT images are fused either by discrete wavelet or curvelet transforms, then the fused result are interpolated by the same algorithms. S...

متن کامل

Image Super-Resolution with Fast Approximate Convolutional Sparse Coding

We present a computationally e cient architecture for image super-resolution that achieves state-of-the-art results on images with large spatial extend. Apart from utilizing Convolutional Neural Networks, our approach leverages recent advances in fast approximate inference for sparse coding. We empirically show that upsampling methods work much better on latent representations than in the origi...

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

ژورنال

عنوان ژورنال: IEEE Access

سال: 2019

ISSN: 2169-3536

DOI: 10.1109/access.2019.2908968