WSN Application Based on Image Compression Using AHAAR Wavelet Transform

Wireless sensor networks (WSNs) require a revolutionary lossy compression picture compression approach known as Adaptive Haar wavelet transform theory due to the limited energy storage capacity of sensors. Battery life may be extended by reducing data transfer. As a consequence, a novel grayscale compression approach has been proposed by this research. Basically, this approach compresses the input picture with the least amount of data loss possible, thereby overcoming the original theory's drawbacks by enhancing compression capabilities while still maintaining the output image's aesthetic appeal. By minimizing the amount of energy needed to convey pictures in WSNs, this study intends for a longer sensor lifespan by reducing the amount of visual information that is lost while compressing images. The compression ratio was put to the test using an image library of universal grayscale pictures. An image's KB size before and after compression, its energy before and after compression, and its post-compression energy usage are all compared.