Abstract
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).
Abstract (translated)
互联网将整个世界变成了一个小村庄，这是因为它使分享数百万图像和视频变得容易。然而，发送和接收大量数据被认为是一个主要挑战。为了解决这一问题，需要一种新算法来减少图像比特数，并以压缩形式代表数据。然而，图像压缩是传输大型文件和图像的重要应用。这需要在这个领域的适当和高效的传输来实现任务并取得最佳结果。在本工作中，我们提出了基于离散哈特利小波变换的新算法，以展示彩色图像的效率和质量。通过压缩彩色图像，这种方法对其进行分析，并将其分为近似系数和细节系数，然后将小波添加到MATLAB中。通过多分辨率分析(MRA)，得出适当的过滤器，并证明通过测试新的过滤器并进行其操作，数学方面得到了验证。在rows的分解和重建过程中，采取过滤器的逆，处理矩阵的 columns，原始矩阵通过测量图像参数来实现最佳图像质量，例如峰值信号-噪声比(PSNR)、压缩比(CR)、像素比特数(BPP)和均方误差(MSE)。
URL
https://arxiv.org/abs/2303.13175
