In this paper, we consider the one-shot version of the classical Wyner-Ziv problem where a source is compressed in a lossy fashion when the decoder has access to a correlated side information. Following the well-known entropy constrained scalar quantization framework, we assume scalar quantization followed by variable length entropy coding. We assume a uniform source, whose compression is shown to be equivalent to compression of simple processes characterized by low-dimensional features within a high-dimensional ambient space, such as images. We find upper and lower bounds to the entropy-distortion functions for quantized and noisy side information, and illustrate that the bounds get tighter as the compression rate increases.