We present a new approach leveraging the Sliding Frank--Wolfe algorithm to address the challenge of line recovery in degraded images. Building upon advances in conditional gradient methods for sparse inverse problems with differentiable measurement models, we propose two distinct models tailored for line detection tasks within the realm of blurred line deconvolution and ridge detection of linear chirps in spectrogram images.

翻译：我们提出了一种利用滑动Frank-Wolfe算法的新方法，以解决退化图像中直线恢复的挑战。基于可微测量模型稀疏逆问题的条件梯度方法的最新进展，我们针对模糊直线反卷积和线性调频信号在时频谱图像中的脊线检测等直线检测任务，提出了两种专用模型。