GaussianImage introduces a novel approach to image representation and compression by utilizing 2D Gaussian Splatting. The method aims to address the limitations of implicit neural representations (INRs) by offering a more efficient paradigm that reduces GPU memory usage, accelerates training, and enhances rendering speed. By representing images with 2D Gaussians, the proposed method achieves high-quality results with minimal parameters, leading to faster decoding speeds and improved compression performance. The innovative accumulated blending mechanism simplifies alpha blending, while merging color coefficients and opacity streamlines the process further. Additionally, a two-step compression pipeline is employed to convert the Gaussian representation into a practical image codec, showcasing competitive rate-distortion performance compared to existing methods like COIN and COIN++. Experimental results demonstrate the effectiveness of each component in enhancing image representation efficiency.
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by Xinjie Zhang... at arxiv.org 03-14-2024
https://arxiv.org/pdf/2403.08551.pdfDeeper Inquiries