WITHDRAWN: A novel generative adversarial block truncation coding schemes for high rated image compression on E-learning resource environment

Abstract

Abstract Image compression is a useful technique that is inevitable to store any images in compressed pattern. The compressed image is reconstructed using image retrieval process for any applications. This technique ensures storage efficiency in various content management applications. Particularly, E-Learning resource environment deals with more space complexity. The E-Learning storage space complexity can be reduced with the help of image compression techniques. There are different types of image compression techniques invented for building compressed resources. Block Truncation Coding (BTC) is a type of lossy compression technique for reducing grey scale quantities using blocking and quantizing phases. This is an effective technique for compressing the images. In extend, Absolute Moment BTC (AMBTC) technique is proposed for minimizing the reconstruction error rate of standard BTC model. The image blocks generation and compression are the main phases of BTC model. This can be applied for both colour images and grey scale images. However, the conventional BTC procedures lacks for edge reconstructions and noise reductions in the output images. This problem creates BTC with lack of inaccuracy in complex image compression platforms such as E-Learning image sources. In the scope, the need for more active and generative image compression procedures is necessary to improve BTC principles. This work proposes highly complex and novel Generative Adversarial BTC (GA-BTC) compression models with multiple variances. GABTC is developed with multi-layered Deep Neural Network (DNN) structures with GA neural models. The integration of both GA models and BTC principles improve the quality of block constructions and reconstructions significantly. This work evaluates the model complexity and efficiency using various E-Learning images (Colour and Grey Scale) with different compression quality measurements.