This paper presents VCMalloc, a custom memory allocator based on a new dynamic memory management approach that keeps data allocated in a contiguous form in memory. It can preserve the virtual contiguity of data even after performing different memory operations like “Reallocation” and “Free” without consuming much system resources. A novel control plane that we call a “Memory Management System” is introduced with a set of algorithms for the physical-virtual memory mappings, assuring fast, efficient, and safe tracking of data and user pointers. The proposed allocator prioritizes virtual contiguity while it keeps the physical memory completely up to the operating system to manage. It was tested and compared with the current implementation of Malloc as well as a state-of-the-art memory allocator MIMalloc in the recent versions of the Microsoft Windows operating system. For the allocator itself, a considerable performance increase has been achieved in basic operations of up to 28% increase in allocation speed and 26% in reallocation speed. The data structures allocated by VCMalloc have shown remarkable performance increases of up to 31% faster for matrix multiplication. Furthermore, VCMalloc has also demonstrated its superiority in real-world SPEC CPU 2017 benchmark applications.

In IKONOS imagery, both multispectral (MS) and panchromatic data are provided, with different spatial resolutions. IKONOS images can be fused or pan-sharpened for the visual interpretation of large-area-scale applications. To date, many image fusion techniques have been developed. In particular, the intensity-hue-saturation (IHS)-based methods are well known in quick image pan-sharpening. However, most of these processes produce color distortion due to the unnatural spectral response of IKONOS sensors, particularly in vegetated areas. Hence, many recent methods make use of vegetation enhancement in order to correct the unnatural color appearance. Generally, this enhancement is accomplished using vegetation indexes (VIs). A new fusion approach that produces images with natural colors is proposed. Moreover, in this technique, a high-resolution normalized difference VI is also proposed and used in delineating the vegetation. The procedure is performed in two steps: MS fusion using the IHS technique and vegetation enhancement. Vegetation enhancement is a correction step, and it depends on the considered application. The new approach provides very good results in terms of objective quality measures. In addition, visual analysis proves that the concept of the proposed approach is promising, and it improves well the fusion quality by enhancing the vegetated zones.