Optical image encryption via photon-counting imaging and compressive sensing based ptychography

Abstract

In this study, we investigate the integration of compressive sensing (CS) and photon-counting imaging (PCI) techniques with a ptychography-based optical image encryption system. Primarily, the plaintext real-valued image is optically encrypted and recorded via a classical ptychography technique. Further, the sparse-based representations of the original encrypted complex data can be produced by combining CS and PCI techniques with the primary encrypted image. Such a combination takes an advantage of reduced encrypted samples (i.e., linearly projected random compressive complex samples and photon-counted complex samples) that can be exploited to realize optical decryption, which inherently serves as a secret key (i.e., independent to encryption phase keys) and makes an intruder attack futile. In addition to this, recording fewer encrypted samples provides a substantial bandwidth reduction in online transmission. We demonstrate that the fewer sparse-based complex samples have adequate information to realize decryption. To the best of our knowledge, this is the first report on integrating CS and PCI with conventional ptychography-based optical image encryption.

Asymmetric Optical Image Encryption With Silhouette Removal Using Interference and Equal Modulus Decomposition

“…Optical image encryption [1]- [16] has made significant advances in recent decades. The interference-based encryption (IBE) scheme [17] proposed by Zhang and Wang is useful for optical image encryption because of its simple structure and an encryption process that does not involve iteration.…”

Cryptographic key distribution over a public network via variance-based watermarking in compressive measurements

“…Fortunately, the newly developed theory of compressed sensing (CS) [10][11][12] provides a new technical solution for DRPE compression during the optical sampling [13], and allows one to accurately reconstruct the signal known a priori to be sparse or compressive from its linear projections, with a sampling rate far below the Nyquist rate [10,11]. Given all these advantages of CS, many methods in optical security field, like Ptychography [14], quick response codes [15], have been recently combined with compressed DRPE to enhance their performance. On the other hand, CS has developed a single-pixel camera [16,17] to acquire wider applications, like in remote sensing [18,19], adaptive ghost imaging [20], biological imaging [21], phase retrieval [22], and so forth.…”

Holey-Cavity-Based Compressive Sensing for Ultrasound Imaging

“…Other software methods, which usually involve novel sampling methods, have been proposed, as well [ 20 , 21 ]. Similar to coded masks that are commonly used in compressive optical imaging [ 22 , 23 , 24 ] as a subgroup of hardware-based methods, Kruizinga et al introduced a rotating mask of randomly-varying thicknesses throughout its surface to randomize ultrasound waves, and they were able to retrieve 3D images of objects using a single transducer [ 25 ]. In this study, a static 2D cavity has been selected as a structure that enables randomization of the wave fields in three generalized dimensions, one spectral and two spatial, thus leading to enhanced ultrasound imaging via compressive sensing.…”