Adaptive Representation of JPEG 2000 Images Using Header-based Processing

Abstract

To bridge the mismatch between the sizes of images and display devices, we present an efficient and automatic algorithm to create an adaptive image representation called SmartNail. Given a digital image and rectangular display frame smaller than the image, we define the SmartNail as an appropriately cropped part of a suitably scaled-down image. We choose the SmartNail-defining parameters - down-scaling factor and cropping location - to maximize a bit-allocation-based cost function that quantifies the visual importance of the image content in the SmartNail. For JPEG 2000-encoded images, the SmartNail parameters can be determined using just the header information available in the encoded file. Hence only the wavelet coefficients required to reconstruct the SmartNail need to be decoded from the entire JPEG 2000 code stream. Consequently, the SmartNail construction requires minimal computations and memory requirements. Simulations demonstrate the effectiveness of SmartNail representations.