The Internet has turned the entire world into a small village;this is because it has made it possible to share millions of images and videos. However, sending and receiving a huge amount of data is considered to be a main challenge. To address this issue, a new algorithm is required to reduce image bits and represent the data in a compressed form. Nevertheless, image compression is an important application for transferring large files and images. This requires appropriate and efficient transfers in this field to achieve the task and reach the best results. In this work, we propose a new algorithm based on discrete Hermite wavelets transformation (DHWT) that shows the efficiency and quality of the color images. By compressing the color image, this method analyzes it and divides it into approximate coefficients and detail coefficients after adding the wavelets into MATLAB. With Multi-Resolution Analyses (MRA), the appropriate filter is derived, and the mathematical aspects prove to be validated by testing a new filter and performing its operation. After the decomposition of the rows and upon the process of the reconstruction, taking the inverse of the filter and dealing with the columns of the matrix, the original matrix is improved by measuring the parameters of the image to achieve the best quality of the resulting image, such as the peak signal-to-noise ratio (PSNR), compression ratio (CR), bits per pixel (BPP), and mean square error (MSE).
翻译:现代互联网已经将整个世界变成了一个小村庄,这是因为它已经使得分享数百万张图片和视频成为可能。然而,发送和接收大量数据被认为是一个主要挑战。为了解决这个问题,需要一种新的算法,以减少图像位数并以压缩形式表示数据。然而,图像压缩是传输大型文件和图像的重要应用。这需要在这个领域中适当和高效的转移来完成任务并达到最佳结果。在这项工作中,我们提出了一种基于离散埃尔米特小波变换(DHWT)的新算法,展示了彩色图像的效率和质量。通过压缩彩色图像,该方法对其进行分析,并在添加小波的情况下将其分为近似系数和细节系数。通过多分辨分析(MRA),得出适当的滤器,并通过测试新滤器及其操作来验证其数学方面的有效性。在行分解后经过重构,取滤波器的逆和处理矩阵的列,通过测量图像参数来改善原始矩阵以获得最佳的结果图像质量,如峰值信噪比(PSNR)、压缩比(CR)、像素每比特数(BPP)和均方误差(MSE)。