Image compression is the technique which reduces the amount of data required to represent a digital image. Statistical properties of the image are used in design an appropriate compression technique. An image compression is used for compression, the good picture quality can be retrieved and also achieves better compression ratio. Also in the past few years Artificial Neural Network becomes popular in the field of image compression. The inputs to the network are the pre-processed data of original image, while the outputs are reconstructed image data, which are close to the inputs. By implementing the proposed scheme the influence of different compression ratios within the scheme is investigated. It has been demonstrated through several experiments to develop a better quality of image compression techniques using Multi-Layer Perceptron (MLP) with wavelet transform coefficients and report its application to image compression by using error metrics like Mean Square Error (MSE) and Peak-Signal-to-Noise Ratio (PSNR).
Wavelet Transformation, Artificial Neural Network, Multi-Layer Perceptron, Mean Square Error and Peak-Signal-to-Noise Ratio
