We present the results of what we believe is the first application of wavelet analysis to the compression of complex-valued digital holograms of three-dimensional real-world objects. We achieve compression through thresholding and quantization of the wavelet coefficients, followed by lossless encoding of the quantized data.

Abstract:We apply two novel nonuniform quantization techniques to digital holograms of three-dimensional real-world objects. Our companding approach, combines the efficiency of uniform quantization with the improved performance of nonuniform quantization. We show that the performance of companding techniques can be comparable with k-means clustering and a competitive neural network, while only requiring a single-pass processing step. The quantized holographic pixels are coded using lossless techniques for the calculation of compression ratio.

Abstract-We present a novel nonuniform quantization compression technique-histogram quantization-for digital holograms of 3-D real-world objects. We exploit a priori knowledge of the distribution of the values in our data. We compare this technique to another histogram based approach: a modified version of Max's algorithm that has been adapted in a straightforward manner to complex-valued 2-D signals. We conclude the compression procedure by applying lossless techniques to our quantized data. We demonstrate improvements over previous results obtained by applying uniform and nonuniform quantization techniques to the hologram data.Index Terms-Digital holography, image compression, nonuniform quantization, 3-D image processing.

Abstract-Compression and encryption/decryption are necessary for secure and efficient storage and transmission of image data. Optical encryption, as a promising application of display devices, takes advantage of both the massive parallelism inherent in optical systems and the flexibility offered by digital electronics. We encrypt real-world three-dimensional (3D) objects, captured using phase-shift interferometry, by combining a phase mask and Fresnel propagation. Compression is achieved by nonuniformly quantizing the complex-valued encrypted digital holograms using an artificial neural network. Decryption is performed by displaying the encrypted hologram and phase mask in an identical configuration. We achieved good quality decryption and reconstruction of 3D objects with as few as 2 bits in each real and imaginary value of the encrypted data.Index Terms-Artificial neural network (ANN), digital holography, image compression, optical encryption, three-dimensional (3D) image processing.