论文标题
通过深符号检索中基于DCT的图像编码中压缩符号信息
Compressing Sign Information in DCT-based Image Coding via Deep Sign Retrieval
论文作者
论文摘要
由于符号的均衡特征，压缩离散余弦变换（DCT）系数的符号信息是图像编码方案中的一个棘手问题。为了克服这一难度，我们为称为“符号检索”的符号信息提出了一种有效的压缩方法。该方法的灵感来自相位检索，这是一个经典的信号恢复问题，它是从其大小中找到离散傅立叶变换系数的相位信息。所有DCT系数的符号信息都从编码器的bitstream中排除，并通过我们的符号检索方法在解码器上进行补充。我们通过实验表明，我们的方法在符号和计算成本的位量方面优于先前的方法。我们的方法以Python语言实现，可从https://github.com/ctsutake/dsr获得。
Compressing the sign information of discrete cosine transform (DCT) coefficients is an intractable problem in image coding schemes due to the equiprobable characteristics of the signs. To overcome this difficulty, we propose an efficient compression method for the sign information called "sign retrieval." This method is inspired by phase retrieval, which is a classical signal restoration problem of finding the phase information of discrete Fourier transform coefficients from their magnitudes. The sign information of all DCT coefficients is excluded from a bitstream at the encoder and is complemented at the decoder through our sign retrieval method. We show through experiments that our method outperforms previous ones in terms of the bit amount for the signs and computation cost. Our method, implemented in Python language, is available from https://github.com/ctsutake/dsr.
