Today, computer is the most general tool for processing digital image. The
computer discussed here could be a laptop, a desktop, a workstation, a server, or a
supercomputer. In addition to computer, the specialized image processing hardware
performs as an optimized hardware for specific image processing task which ranges
from a chip to a front-end subsystem. Depending on the particular task need, the
specification level of a computer or the specialized image processing hardware may
be varied in a broad range.
6.3.2 Image Processing Software
Image processing software usually performs specific task on digital image
processing or computer vision. According to the application range, the image
processing software package could be developed for general purpose and specific
purpose. Adobe Photoshop is one of the representative general image processing
software package which is a popular raster graphics editor to process general images.
On the other hand, some image processing software packages are developed for a
specific purpose such as remotely sensed image processing and medical image
processing. For example, most common image processing systems for remotely
sensed imagery include ERDAS Imagine, ENVI, IDRISI, GRASS GIS etc.; each
system has specific features and capabilities.
Besides software package, the open source image processing library, such as
OpenCV, provides a more flexible way to fulfill the image processing tasks. With the
rapid development of artificial intelligence technology, many open source machine
learning projects, especially the deep learning software/framework (e.g., Caffe,
TensorFlow, Theano, PyTorch), are developed within the past decade. More details
about machine learning–based image processing approaches would be discussed in
Sect. 6.5.
6.3.3 Mobile Device–Based Image Processing
Nowadays, mobile devices such as smartphones and tablets are carrying powerful
mobile operating system, such as iOS and Android, and equipped with highperformance hardware including the CPU (central processing unit), mass storage
memory, high-resolution camera, G-sensor, GPS (global positioning system) module, and fingerprint identification system. These features bring mobile devices
unique advantages for processing agricultural image. One major feature of mobile
device is its portability, which allows users to easily capture, access, manage, and
visualize digital images. Based on the great extensibility of mobile platform, some
mobile apps are developed to facilitate agricultural image processing.
For example, Geofairy, a location-based mobile app which is available on both
iOS and Android platforms, allows users to easily retrieve agricultural data, such as
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C. Zhang and L. Lin
computer discussed here could be a laptop, a desktop, a workstation, a server, or a
supercomputer. In addition to computer, the specialized image processing hardware
performs as an optimized hardware for specific image processing task which ranges
from a chip to a front-end subsystem. Depending on the particular task need, the
specification level of a computer or the specialized image processing hardware may
be varied in a broad range.
6.3.2 Image Processing Software
Image processing software usually performs specific task on digital image
processing or computer vision. According to the application range, the image
processing software package could be developed for general purpose and specific
purpose. Adobe Photoshop is one of the representative general image processing
software package which is a popular raster graphics editor to process general images.
On the other hand, some image processing software packages are developed for a
specific purpose such as remotely sensed image processing and medical image
processing. For example, most common image processing systems for remotely
sensed imagery include ERDAS Imagine, ENVI, IDRISI, GRASS GIS etc.; each
system has specific features and capabilities.
Besides software package, the open source image processing library, such as
OpenCV, provides a more flexible way to fulfill the image processing tasks. With the
rapid development of artificial intelligence technology, many open source machine
learning projects, especially the deep learning software/framework (e.g., Caffe,
TensorFlow, Theano, PyTorch), are developed within the past decade. More details
about machine learning–based image processing approaches would be discussed in
Sect. 6.5.
6.3.3 Mobile Device–Based Image Processing
Nowadays, mobile devices such as smartphones and tablets are carrying powerful
mobile operating system, such as iOS and Android, and equipped with highperformance hardware including the CPU (central processing unit), mass storage
memory, high-resolution camera, G-sensor, GPS (global positioning system) module, and fingerprint identification system. These features bring mobile devices
unique advantages for processing agricultural image. One major feature of mobile
device is its portability, which allows users to easily capture, access, manage, and
visualize digital images. Based on the great extensibility of mobile platform, some
mobile apps are developed to facilitate agricultural image processing.
For example, Geofairy, a location-based mobile app which is available on both
iOS and Android platforms, allows users to easily retrieve agricultural data, such as
86
C. Zhang and L. Lin