针对基于编-解码器网络的图像隐写方案生成的含密图像和消息图像质量不高的问题，提出了一种新的基于密集残差连接的编码器-解码器隐写方案，与现有的端到端图像隐写网络不同，所提方案无须对图像进行预处理，采用密集残差连接，将浅层网络的特征输送到深层网络结构的每一层，有效地保留了特征图的细节信息，并使用通道和空间注意力模块对特征进行筛选，提高了编-解码器对图像复杂纹理区域的关注度。在LFW、PASCAL-VOC12和ImageNet数据集的实验结果表明，在保证算法安全性的前提下，所提方法能够有效提高图像质量，含密图像和载体图像的峰值信噪比（peak signal-to-noise ratio, PSNR）和结构相似性（structural similarity, SSIM）的平均值最高达到了36.2 dB和0.98。

A new encod-decoder steganography scheme based on dense residual connection was proposed to solve the problem of poor quality of encod-decoder images and message images generated by image steganography schemes based on encoder-decoder networks. Different from the existing end-to-end image steganography networks, the proposed scheme does not need to preprocess the image, and adopts dense residual connections to transport the features of the shallow network to each layer of the deep network structure, effectively preserving the details of the feature map, and uses channels and spatial attention modules to filter the features, improving the codec's attention to the complex texture region of the image. Experimental results on LFW, PASCAL-VOC12 and ImageNet datasets show that the proposed method can effectively improve image quality under the premise of ensuring the security of the algorithm, including the peak signal-to-noise ratio of dense images and carrier images. The mean values of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) are 36.2 dB and 0.98 respectively.