Nowadays, a major problem in faster page loading through optimizing websites is the absence of having images in their intended sizes. Accordingly, while loading a webpage, most of the time overhead pertains to image-related tasks such as image loading and resizing, which can be optimized substantially through the pre-availability of smaller-size images. Therefore, in this study, we propose a strategy to enable faster and efficient image retrieval from a cloud via the necessary pre-processing of images beyond conventional online processing. We also extend the abilities of cloud file sharing from the conventional “only storing images” to pre-processing along with security reinforcing. Here, we perform the first task of resizing images to several dimensions for covering diversified remote user devices available nowadays. Then, we perform encoding and encryption of images using the P-Fibonacci transform of Discrete Cosine Coefficients (PFCC) algorithm. Afterward, we resize images using the Bicubic interpolation method to both JPEG and Progressive-JPEG (PJPEG) formats by adding a new middleware named iBuck for faster and smooth retrieval. We leverage necessary algorithms and image types after careful evaluation of their performances in our intended framework. Our evaluation covers both objective and subjective evaluations including QoE metrics such as MSE, SSIM, etc. Furthermore, we conduct detailed experimentation over real setups to evaluate the performance of our implemented middleware in a cloud file sharing environment with both custom and standard data sets. Our evaluation reveals substantial performance improvement using our proposed framework compared to that using conventional alternatives.

如今，通过优化网站来加快页面加载速度的一个主要问题是缺少预期尺寸的图像。因此，在加载网页时，大部分时间开销都与图像相关的任务有关，例如图像加载和调整大小，这些任务可以通过预先提供较小尺寸的图像进行实质性优化。因此，在这项研究中，我们提出了一种策略，通过对传统在线处理之外的图像进行必要的预处理，从云中实现更快、更有效的图像检索。我们还将云文件共享的能力从传统的“仅存储图像”扩展到预处理和安全加固。在这里，我们执行第一个任务，将图像调整为多个维度，以覆盖当今可用的各种远程用户设备。然后，我们使用离散余弦系数 (PFCC) 算法的 P-Fibonacci 变换对图像进行编码和加密。之后，我们通过添加名为 iBuck 的新中间件，使用双三次插值方法将图像大小调整为 JPEG 和渐进式 JPEG (PJPEG) 格式，以实现更快、更流畅的检索。在仔细评估它们在我们预期框架中的性能后，我们利用必要的算法和图像类型。我们的评估涵盖客观和主观评估，包括 QoE 指标，如 MSE、SSIM 等。此外，我们对真实设置进行了详细实验，以评估我们实施的中间件在具有自定义和标准数据集的云文件共享环境中的性能。