DG-LIC-CAN Allicdata Electronics
Allicdata Part #:

DG-LIC-CAN-ND

Manufacturer Part#:

DG-LIC-CAN

Price: $ 0.00
Product Category:

Uncategorized

Manufacturer: Digi International
Short Description: MODULE
More Detail: N/A
DataSheet: DG-LIC-CAN datasheetDG-LIC-CAN Datasheet/PDF
Quantity: 1000
1 +: 0.00000
Stock 1000Can Ship Immediately
$ 0
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Series: *
Part Status: Obsolete
Description

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Data Generating-Logarithmic Image Compression (DG-LIC) is a technique developed in the field of digital image processing. It was first introduced in 1999 and has since become widely used in the fields of telecommunication, medical imaging, automotive, and gaming. This technology is a powerful tool for encoding visual information into compact binary form for transmission or storage. It allows for efficient transmission of images over networks with limited bandwidth while preserving the information content and quality.

In its basic form, the DG-LIC algorithm breaks an image into small blocks, which are then converted to binary form by the use of a logarithmic compression function. This function reduces the dynamic range of an image while preserving the information content contained in each individual block. The algorithm then proceeds to the next part of the encoding process, which involves application of a mask to the binary representation of each block. This mask is used to redistribute the binary representation of each block according to the groups present in that particular region of the image.

The key benefit of the DG-LIC technique is that it allows for a much more efficient representation of an image compared to other image compression schemes like JPEG and GIF. By taking advantage of the small number of groups present in most images, the DG-LIC algorithm is able to reduce the number of bits required to represent an image. This results in a more compressed image with a higher image compression ratio. This improved compression ratio translates into a much smaller image file size which is much more suitable for applications such as transmission and streaming.

The DG-LIC technique is also beneficial in terms of computational complexity. In particular, the encoding process is lightning fast and can be performed in real-time. This makes the DG-LIC technology a popular choice for applications where time is of the essence, such as video streaming. Moreover, since the DG-LIC algorithm does not require any additional hardware components, its cost-effectiveness makes it an ideal choice for applications that require high-quality images with minimal overhead.

The DG-LIC technique has been used in many different applications, ranging from medical imaging and gaming to automotive and industrial processing. In the field of medical imaging, the technique is used for transmission of MRI and CT-scan images, allowing for faster transmission times without sacrificing image quality. In gaming applications, the technology is commonly incorporated in image processing pipelines that generate realistic 3D environments. In automobiles, the technology is used in advanced driver assistance systems for improved collision avoidance.

The DG-LIC technique has also been used in industrial processing, such as 3D printing and robotic navigation. The algorithm allows for faster and more efficient 3D printing by allowing a printer to rapidly reference its data when generating the object. Additionally, it has been used in robotic navigation in order to speed up robotic processing times and reduce the complexity of motion planning.

In conclusion, the application field and working principle of Data Generating-Logarithmic Image Compression (DG-LIC) is a powerful technology that is used in a variety of applications. Its ability to reduce the bits required to represent an image allows for improved compression ratios and faster transmission times. Additionally, its ability to compress images without sacrificing image quality makes it a cost-effective and efficient solution for a variety of applications and industries. The DG-LIC technique is an invaluable tool for the modern digital landscape and will likely remain an important tool for the foreseeable future.

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