The effect of temporal recursive filtering and frame rate reduction on a sequence of moving images is investigated. Following a well-known first-order Markov model for the temporal domain data, the effect of filtering and frame rate reduction on the values of variance, correlation coefficient, filtering distortion, and interframe prediction error are mathematically derived. The validity of these derivations is verified by the experimental results using a CCITT standard sequence which closely follows the first-order Markov model. The effect of temporal filtering and frame rate reduction to the coding rate is examined by encoding the CCITT standard sequence using a combined interframe and intraframe Scene Adaptive Coding system. At a frame rate of 30 frames per second, a 2:1 reduction in coding rate is obtained with a filtering coefficient of 0.5. At a frame rate of 10 frames per second, an additional reduction factor of nearly 2 is obtained using the same filtering coefficient. Selected images are presented to demonstrate the subjective effect.

An efficient single-pass adaptive bandwidth compression technique using the discrete cosine transform is described. The coding process involves a simple thresholding and normalization operation on the transform coefficients. Adaptivity is achieved by using a rate buffer for channel rate equalization. The buffer status and input rate are monitored to generate a feedback normalization factor. Excellent results are demonstrated for coding of color images at 0.4 bits/pixel corresponding to real-time color television transmission over a 1.5 Mbit/s channel.

An efficient adaptive encoding technique using a new implementation of the Fast Discrete Cosine Transform (FDCT) for bandwidth compression of monochrome and color images is described. Practical system application is attained by maintaining a balance between complexity of implementation and performance. FDCT sub-blocks are sorted into four classes according to level of image activity, measured by the total ac energy within each sub-block. Adaptivity is provided by distributing bits between classes, favoring higher levels of activity over lower levels. Excellent performance is demonstrated in terms of mean square error and direct comparison of original and reconstructed images. Results are presented for both noiseless and noisy transmission at a total rate of 1 bit and 0.5 bit per pixel for a monochrome image and for a total rate of 2 bits and 1 bit per pixel for a color image. In every case the total bit rate includes all overhead required for image reconstruction and bit protection.

A Fast Discrete Cosine Transform algorithm has been developed which provides a factor of six improvement in computational complexity when compared to conventional Discrete Cosine Transform algorithms using the Fast Fourier Transform. The algorithm is derived in the form of matrices and illustrated by a signal-flow graph, which may be readily translated to hardware or software implementations.

A new unitary transform called the slant transform, specifically designed for image coding, has been developed. The transformation possesses a discrete sawtoothlike basis vector which efficiently represents linear brightness variations along an image line. A fast computational algorithm has been found for the transformation. The slant transformation has been utilized in several transform image-coding systems for monochrome and color images. Computer simulation results indicate that good quality coding can be accomplished with about 1 to 2 bits/pixel for monochrome images and 2 to 3 bits/pixel for color images.