Theresia Lumbantobing

Implementasi Metode Felics Pada Kompresi Citra Format GIF

Introduction

Implementasi metode felics pada kompresi citra format gif. Implementasi metode FELICS untuk kompresi citra GIF lossless yang cepat dan efisien. Kurangi ukuran file gambar, hemat penyimpanan & bandwidth dengan teknik ini.

Abstract

At this time, the increasingly rapid development of science and technology makes two-dimensional image files very necessary, where the resulting image size is large, requiring very large storage media, and other problems arise when exchanging data and information which increasingly consumes time and bandwidth. Therefore, a solution to the problem above emerged, namely by data compression. Data compression or data compression is a way in computer science to require smaller storage space, so that storage is more efficient. This is a compression method designed for grayscale images. The FELICS method presents a simpler system for lossless image compression that runs very quickly and only loses minimal compression efficiency. Implementation is the application or implementation, as an action to carry out the plan that has been made.

Review

This paper proposes an implementation of the FELICS method for compressing GIF image files, addressing the common issue of large image sizes consuming significant storage and bandwidth. The abstract effectively introduces the problem of data volume in two-dimensional images and positions data compression as a necessary solution for efficient storage and data exchange. The choice of the FELICS method is highlighted, noting its claims of simplicity, speed, and minimal loss in compression efficiency, particularly for lossless image compression. The title clearly indicates the practical "implementation" aspect, suggesting a focus on applying this method to a specific and widely used image format. The core strength of the described work lies in its practical application to a relevant problem. The stated benefits of the FELICS method – a simpler system, high speed, and minimal compression efficiency loss – are attractive attributes for any compression algorithm. Should the implementation successfully demonstrate these advantages when applied to GIF images, it would offer a valuable contribution to the field of image processing and data efficiency. The focus on implementation suggests that the paper will provide empirical results and insights into the performance of FELICS in a real-world scenario with a common image format. However, the abstract could benefit from greater specificity regarding the implementation and its expected outcomes. Notably, FELICS is described as a method "designed for grayscale images," which presents a potential mismatch when applied to the GIF format, which often supports indexed color. It would be crucial for the full paper to clarify how FELICS is adapted or applied to GIF images—whether it specifically targets grayscale GIFs, processes color channels independently, or involves a preliminary color-to-grayscale conversion. Furthermore, the abstract lacks specific metrics or expected quantitative results (e.g., typical compression ratios, processing speed improvements compared to existing methods) that would establish the novelty and impact of the implementation. Providing these details would significantly strengthen the paper's contribution and allow readers to better assess its value.

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