Image compression using artificial neural network

Anjana, B.; Shreeja, R

doi:10.1049/cp.2012.2551

Cited by 5 publications

(1 citation statement)

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“…Neural network divides the images into subdivision parts, i.e., into the blocks and pixels can be shown in a gray level values within the block, and the input will be given to the neural network through this system. This technique can help to find out the efficient multi-layered neural networks [5]. With the advancement of different multimedia service in computer and media transmission applications, for example, digital broadcasting, teleconferencing, and video technology; hence there is need of Image compression.…”

Section: VImentioning

confidence: 99%

Full Resolution Image Compression with Deep Neural Networks

Grewal¹

2017

IJRASET

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Image compression became prevalent for every image and graphic that we want to send over the internet. It is because a significant amount of bandwidth and space decrease using the image compression techniques. It reduces both time and bandwidth cost and leads to fast and efficient sharing of images and other information. Neural networks have been researching rapidly for image processing. In this research, we presented image compression and error correction control using deep neural networks. First, Deep Neural Network (DNN) is implemented for image compression. We applied the algorithm on four different sizes of images including 512*512, 256*256, 128*128 and 64*64. The result of DNN implementation shows better quality of the decompressed images along with less computational capacity. The proposed algorithm is effective in accomplishing better errorcorrection and reducing the storage requirements.

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Section: VImentioning

confidence: 99%