Optical analog computing has attracted intensive attention recently because it holds the promise to tackle the issues of low speed, high power consumption, and complexity in traditional digital signal processing with electric solutions, especially for the scenarios that require real-time and high throughput [1–3]. As an efficient platform for realizing optical analog computing, artificially engineered photonic structures have been proposed and demonstrated to perform spatial differentiation, integration, convolution, even equation solving, and so on [4–9]. Of particular importance, differentiation is one of the most fundamental mathematical operations, and its realization has gained much research interest. Various principles have been exploited, including metasurface [10–16], Brewster effect [17,18], and surface plasmon polariton [19–22], among others [23–28]. By employing the optical analog differentiation on spatial functions, edge detection and further processing for images can be conducted in an efficient manner [29–33]. Therefore, optical analog computing can facilitate the development of image-processing technology together with electronic platforms.