Daksha is a proposed high-energy transient mission for the study of electromagnetic counterparts of gravitational wave sources and gamma-ray bursts. Ideally, such studies need good localization of the GRBs along with their detection itself. In its current configuration, Daksha can localize short-duration bursts (T \(_{90}\) <1s) up to the fluence >1 \(\times 10^{-7}~\mathrm {erg~cm^{-2}}\) to within 5 \(^{\circ }\) —10 \(^{\circ }\) using projection method. However, for rapid optical follow-up observations, the localization error radius should preferably be smaller than the field of view (FOV) of most optical telescopes, which is typically < 1 \(^{\circ }\) . Thus it would be greatly advantageous if the onboard localization by Daksha is within 1 \(^{\circ }\) . One possibility to improve localization capability of Daksha is by employing coded mask imaging technique, which is being investigated in this work. Daksha carries three types of detectors mounted on the hemispherical dome of the payload; low-energy (LE), medium-energy (ME) and high-energy (HE) detectors. The LE and ME detectors are placed on the outside surface of the dome, while HE detectors are housed inside. The ME detector package (MEP) with its pixellated CZT detectors is a natural choice for attempting coded mask imaging, but it may lead to loss of sensitivity (by about a factor of five) and might require additional size and weight. In this context, here we explore the feasibility of using coded aperture mask (CAM) with the LE detector package (LEP), without substantially changing the size of the overall dome structure of Daksha. We consider a few candidate detectors, such as 1-D position sensitive silicon drift detectors (SDDs) as well as 2-D position sensitive X-ray Charge-Coupled Devices (CCDs), reported in the recent literature. We find that it is technically feasible to conceive a coded mask telescope (CMT) using these detectors that can provide sensitivity and localization accuracy of 4 \(\times 10^{-7}~\mathrm {erg~cm^{-2}}\) and \(\sim 0.7^{\circ }\) respectively in the best case, and 8 \(\times 10^{-7}~\mathrm {erg~cm^{-2}}\) and \(\sim 1.8^{\circ }\) respectively in the worst case.