The present work proposes an encoder for image transmission via LoRa communication modules. These enable long-range, low-power transmission schemes and are ideal for monitoring in places with no mobile network connectivity. Nonetheless, this technology has a low transmission bitrate, which limits its use to high bandwidth applications. The state-of-the-art has numerous image encoders, but few achieve an adequate balance between image quality, compression, sequential decoding, and computational complexity. The proposed encoder uses the YCoCg color model and chromatic subsampling followed by wavelet subband decomposition, which extracts relevant subbands in the image to then reconstruct it sequentially. Each subband is quantized independently and then enters an adaptive entropic encoder. This encoder is compared to the JPEG2000 encoder using the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) quality metrics. Results show that the proposal obtains a reconstructed image quality close to that of JPEG2000 with a higher compression rate. Moreover, it improves the transmission time of images through a LoRa link by 99.09%.