An Introduction to Image Sharpening Tools in SAGA GIS

Purpose

The purpose of this tutorial is to introduce the concepts behind image sharpening of remotely sensed imagery and provide step-by step instructions for applying four methods using SAGA GIS software. In addition, this tutorial will aim to expand on the basic information and techniques presented.

Note: This tutorial assumes the user has some general knowledge in the field of remote sensing. Introductory information can be found online, and a recommended (detailed) text is John R. Jensen’s “Remote Sensing of the Environment: and Earth Resource Perspective”.

Introduction

Remote Sensing Image Sharpening

What is image sharpening?

Image sharpening is a method that has developed out of one of the balancing acts inherent to remotely sensed imagery: the trade-off between spectral resolution and spatial resolution.

Multispectral imagery sensors record detailed information in several spectral bands (red, green , blue, near-infrared, etc.), but at the cost of reduced spatial resolution. For example, the Landsat-series of satellites multispectral channels have a spatial resolution of 30 metres. In comparison, panchromatic imagery sensors record all spectral information in one band, allowing it to collect more spatial details (increased spatial resolution) at the cost of spectral information (ex: panchromatic imagery is in greyscale, not colour). For example, the Orbview3 satellite collects panchromatic images at a 1 metre spatial resolution.

Image sharpening is designed to combine the best of both worlds: multispectral imagery with high spectral resolution (colour, near-infrared, etc.) but lower spatial resolution, and panchromatic imagery with low spectral resolution (greyscale) but higher spectral resolution into one image with both high spectral and spatial resolution.